m8than commited on
Commit
c5ec1e7
·
verified ·
1 Parent(s): 295daa0

Upload folder using huggingface_hub

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
chat_template.jinja ADDED
@@ -0,0 +1,87 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if messages[0]["role"] == "system" %}
2
+ {%- set system_message = messages[0]["content"] %}
3
+ {%- set loop_messages = messages[1:] %}
4
+ {%- else %}
5
+ {%- set loop_messages = messages %}
6
+ {%- endif %}
7
+ {%- if not tools is defined %}
8
+ {%- set tools = none %}
9
+ {%- endif %}
10
+ {%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
11
+
12
+ {#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
13
+ {%- set ns = namespace() %}
14
+ {%- set ns.index = 0 %}
15
+ {%- for message in loop_messages %}
16
+ {%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
17
+ {%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
18
+ {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
19
+ {%- endif %}
20
+ {%- set ns.index = ns.index + 1 %}
21
+ {%- endif %}
22
+ {%- endfor %}
23
+
24
+ {{- bos_token }}
25
+ {%- for message in loop_messages %}
26
+ {%- if message["role"] == "user" %}
27
+ {%- if tools is not none and (message == user_messages[-1]) %}
28
+ {{- "[AVAILABLE_TOOLS][" }}
29
+ {%- for tool in tools %}
30
+ {%- set tool = tool.function %}
31
+ {{- '{"type": "function", "function": {' }}
32
+ {%- for key, val in tool.items() if key != "return" %}
33
+ {%- if val is string %}
34
+ {{- '"' + key + '": "' + val + '"' }}
35
+ {%- else %}
36
+ {{- '"' + key + '": ' + val|tojson }}
37
+ {%- endif %}
38
+ {%- if not loop.last %}
39
+ {{- ", " }}
40
+ {%- endif %}
41
+ {%- endfor %}
42
+ {{- "}}" }}
43
+ {%- if not loop.last %}
44
+ {{- ", " }}
45
+ {%- else %}
46
+ {{- "]" }}
47
+ {%- endif %}
48
+ {%- endfor %}
49
+ {{- "[/AVAILABLE_TOOLS]" }}
50
+ {%- endif %}
51
+ {%- if loop.last and system_message is defined %}
52
+ {{- "[INST]" + system_message + "\n\n" + message["content"] + "[/INST]" }}
53
+ {%- else %}
54
+ {{- "[INST]" + message["content"] + "[/INST]" }}
55
+ {%- endif %}
56
+ {%- elif (message.tool_calls is defined and message.tool_calls is not none) %}
57
+ {{- "[TOOL_CALLS][" }}
58
+ {%- for tool_call in message.tool_calls %}
59
+ {%- set out = tool_call.function|tojson %}
60
+ {{- out[:-1] }}
61
+ {%- if not tool_call.id is defined or tool_call.id|length != 9 %}
62
+ {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
63
+ {%- endif %}
64
+ {{- ', "id": "' + tool_call.id + '"}' }}
65
+ {%- if not loop.last %}
66
+ {{- ", " }}
67
+ {%- else %}
68
+ {{- "]" + eos_token }}
69
+ {%- endif %}
70
+ {%- endfor %}
71
+ {%- elif message["role"] == "assistant" %}
72
+ {{- message["content"] + eos_token}}
73
+ {%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
74
+ {%- if message.content is defined and message.content.content is defined %}
75
+ {%- set content = message.content.content %}
76
+ {%- else %}
77
+ {%- set content = message.content %}
78
+ {%- endif %}
79
+ {{- '[TOOL_RESULTS]{"content": ' + content|string + ", " }}
80
+ {%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
81
+ {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
82
+ {%- endif %}
83
+ {{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
84
+ {%- else %}
85
+ {{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
86
+ {%- endif %}
87
+ {%- endfor %}
config.json ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "MistralForCausalLM"
4
+ ],
5
+ "attention_dropout": 0.0,
6
+ "bos_token_id": 131072,
7
+ "eos_token_id": 131073,
8
+ "head_dim": 128,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 5120,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 14336,
13
+ "max_position_embeddings": 131072,
14
+ "model_type": "mistral",
15
+ "num_attention_heads": 32,
16
+ "num_hidden_layers": 40,
17
+ "num_key_value_heads": 8,
18
+ "rms_norm_eps": 1e-05,
19
+ "rope_theta": 1000000.0,
20
+ "sliding_window": null,
21
+ "tie_word_embeddings": false,
22
+ "torch_dtype": "bfloat16",
23
+ "transformers_version": "4.55.4",
24
+ "use_cache": false,
25
+ "vocab_size": 131074
26
+ }
generation_config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 1,
4
+ "do_sample": true,
5
+ "eos_token_id": 2,
6
+ "transformers_version": "4.55.4"
7
+ }
model-00001-of-00005.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:341d9f2f7f6345dff49cb5e2980c3f06a67ea1fa0166b79933387d4d0e7ffbf1
3
+ size 4865542976
model-00002-of-00005.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ecd7ead7d90f84080487b7323d5c31c26ce62db0b2b2336c6e1a2053a394f714
3
+ size 4907529424
model-00003-of-00005.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:330b1f8840f22f55a24203ec7f9b8f388ec87d4c9a29db75c8a184130eccff56
3
+ size 4907529456
model-00004-of-00005.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:eb65a2c1ed9cd02ebe4686852743e0677f7327d6073be0866b703251dfffb1ff
3
+ size 4907529456
model-00005-of-00005.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:50fd83fcd1a0279b935a27d7f092c30b0ef01339733903aadaf48358f0e27f52
3
+ size 4907516752
model.safetensors.index.json ADDED
@@ -0,0 +1,371 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_parameters": 12247802880,
4
+ "total_size": 24495605760
5
+ },
6
+ "weight_map": {
7
+ "lm_head.weight": "model-00005-of-00005.safetensors",
8
+ "model.embed_tokens.weight": "model-00001-of-00005.safetensors",
9
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00005.safetensors",
10
+ "model.layers.0.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
11
+ "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
12
+ "model.layers.0.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
13
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
14
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
15
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
16
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
17
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
18
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00005.safetensors",
19
+ "model.layers.1.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
20
+ "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
21
+ "model.layers.1.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
22
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
23
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
24
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
25
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
26
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
27
+ "model.layers.10.input_layernorm.weight": "model-00002-of-00005.safetensors",
28
+ "model.layers.10.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
29
+ "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
30
+ "model.layers.10.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
31
+ "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
32
+ "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
33
+ "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
34
+ "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
35
+ "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
36
+ "model.layers.11.input_layernorm.weight": "model-00002-of-00005.safetensors",
37
+ "model.layers.11.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
38
+ "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
39
+ "model.layers.11.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
40
+ "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
41
+ "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
42
+ "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
43
+ "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
44
+ "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
45
+ "model.layers.12.input_layernorm.weight": "model-00002-of-00005.safetensors",
46
+ "model.layers.12.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
47
+ "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
48
+ "model.layers.12.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
49
+ "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
50
+ "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
51
+ "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
52
+ "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
53
+ "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
54
+ "model.layers.13.input_layernorm.weight": "model-00002-of-00005.safetensors",
55
+ "model.layers.13.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
56
+ "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
57
+ "model.layers.13.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
58
+ "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
59
+ "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
60
+ "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
61
+ "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
62
+ "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
63
+ "model.layers.14.input_layernorm.weight": "model-00002-of-00005.safetensors",
64
+ "model.layers.14.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
65
+ "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
66
+ "model.layers.14.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
67
+ "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
68
+ "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
69
+ "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
70
+ "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
71
+ "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
72
+ "model.layers.15.input_layernorm.weight": "model-00003-of-00005.safetensors",
73
+ "model.layers.15.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
74
+ "model.layers.15.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
75
+ "model.layers.15.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
76
+ "model.layers.15.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
77
+ "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
78
+ "model.layers.15.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
79
+ "model.layers.15.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
80
+ "model.layers.15.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
81
+ "model.layers.16.input_layernorm.weight": "model-00003-of-00005.safetensors",
82
+ "model.layers.16.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
83
+ "model.layers.16.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
84
+ "model.layers.16.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
85
+ "model.layers.16.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
86
+ "model.layers.16.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
87
+ "model.layers.16.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
88
+ "model.layers.16.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
89
+ "model.layers.16.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
90
+ "model.layers.17.input_layernorm.weight": "model-00003-of-00005.safetensors",
91
+ "model.layers.17.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
92
+ "model.layers.17.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
93
+ "model.layers.17.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
94
+ "model.layers.17.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
95
+ "model.layers.17.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
96
+ "model.layers.17.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
97
+ "model.layers.17.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
98
+ "model.layers.17.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
99
+ "model.layers.18.input_layernorm.weight": "model-00003-of-00005.safetensors",
100
+ "model.layers.18.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
101
+ "model.layers.18.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
102
+ "model.layers.18.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
103
+ "model.layers.18.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
104
+ "model.layers.18.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
105
+ "model.layers.18.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
106
+ "model.layers.18.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
107
+ "model.layers.18.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
108
+ "model.layers.19.input_layernorm.weight": "model-00003-of-00005.safetensors",
109
+ "model.layers.19.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
110
+ "model.layers.19.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
111
+ "model.layers.19.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
112
+ "model.layers.19.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
113
+ "model.layers.19.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
114
+ "model.layers.19.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
115
+ "model.layers.19.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
116
+ "model.layers.19.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
117
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00005.safetensors",
118
+ "model.layers.2.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
119
+ "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
120
+ "model.layers.2.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
121
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
122
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
123
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
124
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
125
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
126
+ "model.layers.20.input_layernorm.weight": "model-00003-of-00005.safetensors",
127
+ "model.layers.20.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
128
+ "model.layers.20.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
129
+ "model.layers.20.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
130
+ "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
131
+ "model.layers.20.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
132
+ "model.layers.20.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
133
+ "model.layers.20.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
134
+ "model.layers.20.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
135
+ "model.layers.21.input_layernorm.weight": "model-00003-of-00005.safetensors",
136
+ "model.layers.21.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
137
+ "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
138
+ "model.layers.21.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
139
+ "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
140
+ "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
141
+ "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
142
+ "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
143
+ "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
144
+ "model.layers.22.input_layernorm.weight": "model-00003-of-00005.safetensors",
145
+ "model.layers.22.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
146
+ "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
147
+ "model.layers.22.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
148
+ "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
149
+ "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
150
+ "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
151
+ "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
152
+ "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
153
+ "model.layers.23.input_layernorm.weight": "model-00003-of-00005.safetensors",
154
+ "model.layers.23.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
155
+ "model.layers.23.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
156
+ "model.layers.23.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
157
+ "model.layers.23.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
158
+ "model.layers.23.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
159
+ "model.layers.23.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
160
+ "model.layers.23.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
161
+ "model.layers.23.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
162
+ "model.layers.24.input_layernorm.weight": "model-00004-of-00005.safetensors",
163
+ "model.layers.24.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
164
+ "model.layers.24.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
165
+ "model.layers.24.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
166
+ "model.layers.24.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
167
+ "model.layers.24.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
168
+ "model.layers.24.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
169
+ "model.layers.24.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
170
+ "model.layers.24.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
171
+ "model.layers.25.input_layernorm.weight": "model-00004-of-00005.safetensors",
172
+ "model.layers.25.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
173
+ "model.layers.25.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
174
+ "model.layers.25.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
175
+ "model.layers.25.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
176
+ "model.layers.25.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
177
+ "model.layers.25.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
178
+ "model.layers.25.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
179
+ "model.layers.25.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
180
+ "model.layers.26.input_layernorm.weight": "model-00004-of-00005.safetensors",
181
+ "model.layers.26.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
182
+ "model.layers.26.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
183
+ "model.layers.26.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
184
+ "model.layers.26.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
185
+ "model.layers.26.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
186
+ "model.layers.26.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
187
+ "model.layers.26.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
188
+ "model.layers.26.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
189
+ "model.layers.27.input_layernorm.weight": "model-00004-of-00005.safetensors",
190
+ "model.layers.27.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
191
+ "model.layers.27.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
192
+ "model.layers.27.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
193
+ "model.layers.27.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
194
+ "model.layers.27.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
195
+ "model.layers.27.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
196
+ "model.layers.27.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
197
+ "model.layers.27.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
198
+ "model.layers.28.input_layernorm.weight": "model-00004-of-00005.safetensors",
199
+ "model.layers.28.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
200
+ "model.layers.28.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
201
+ "model.layers.28.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
202
+ "model.layers.28.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
203
+ "model.layers.28.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
204
+ "model.layers.28.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
205
+ "model.layers.28.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
206
+ "model.layers.28.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
207
+ "model.layers.29.input_layernorm.weight": "model-00004-of-00005.safetensors",
208
+ "model.layers.29.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
209
+ "model.layers.29.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
210
+ "model.layers.29.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
211
+ "model.layers.29.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
212
+ "model.layers.29.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
213
+ "model.layers.29.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
214
+ "model.layers.29.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
215
+ "model.layers.29.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
216
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00005.safetensors",
217
+ "model.layers.3.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
218
+ "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
219
+ "model.layers.3.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
220
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
221
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
222
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
223
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
224
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
225
+ "model.layers.30.input_layernorm.weight": "model-00004-of-00005.safetensors",
226
+ "model.layers.30.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
227
+ "model.layers.30.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
228
+ "model.layers.30.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
229
+ "model.layers.30.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
230
+ "model.layers.30.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
231
+ "model.layers.30.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
232
+ "model.layers.30.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
233
+ "model.layers.30.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
234
+ "model.layers.31.input_layernorm.weight": "model-00004-of-00005.safetensors",
235
+ "model.layers.31.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
236
+ "model.layers.31.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
237
+ "model.layers.31.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
238
+ "model.layers.31.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
239
+ "model.layers.31.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
240
+ "model.layers.31.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
241
+ "model.layers.31.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
242
+ "model.layers.31.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
243
+ "model.layers.32.input_layernorm.weight": "model-00004-of-00005.safetensors",
244
+ "model.layers.32.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
245
+ "model.layers.32.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
246
+ "model.layers.32.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
247
+ "model.layers.32.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
248
+ "model.layers.32.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
249
+ "model.layers.32.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
250
+ "model.layers.32.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
251
+ "model.layers.32.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
252
+ "model.layers.33.input_layernorm.weight": "model-00005-of-00005.safetensors",
253
+ "model.layers.33.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
254
+ "model.layers.33.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
255
+ "model.layers.33.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
256
+ "model.layers.33.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
257
+ "model.layers.33.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
258
+ "model.layers.33.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
259
+ "model.layers.33.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
260
+ "model.layers.33.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
261
+ "model.layers.34.input_layernorm.weight": "model-00005-of-00005.safetensors",
262
+ "model.layers.34.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
263
+ "model.layers.34.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
264
+ "model.layers.34.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
265
+ "model.layers.34.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
266
+ "model.layers.34.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
267
+ "model.layers.34.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
268
+ "model.layers.34.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
269
+ "model.layers.34.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
270
+ "model.layers.35.input_layernorm.weight": "model-00005-of-00005.safetensors",
271
+ "model.layers.35.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
272
+ "model.layers.35.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
273
+ "model.layers.35.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
274
+ "model.layers.35.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
275
+ "model.layers.35.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
276
+ "model.layers.35.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
277
+ "model.layers.35.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
278
+ "model.layers.35.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
279
+ "model.layers.36.input_layernorm.weight": "model-00005-of-00005.safetensors",
280
+ "model.layers.36.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
281
+ "model.layers.36.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
282
+ "model.layers.36.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
283
+ "model.layers.36.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
284
+ "model.layers.36.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
285
+ "model.layers.36.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
286
+ "model.layers.36.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
287
+ "model.layers.36.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
288
+ "model.layers.37.input_layernorm.weight": "model-00005-of-00005.safetensors",
289
+ "model.layers.37.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
290
+ "model.layers.37.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
291
+ "model.layers.37.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
292
+ "model.layers.37.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
293
+ "model.layers.37.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
294
+ "model.layers.37.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
295
+ "model.layers.37.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
296
+ "model.layers.37.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
297
+ "model.layers.38.input_layernorm.weight": "model-00005-of-00005.safetensors",
298
+ "model.layers.38.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
299
+ "model.layers.38.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
300
+ "model.layers.38.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
301
+ "model.layers.38.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
302
+ "model.layers.38.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
303
+ "model.layers.38.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
304
+ "model.layers.38.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
305
+ "model.layers.38.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
306
+ "model.layers.39.input_layernorm.weight": "model-00005-of-00005.safetensors",
307
+ "model.layers.39.mlp.down_proj.weight": "model-00005-of-00005.safetensors",
308
+ "model.layers.39.mlp.gate_proj.weight": "model-00005-of-00005.safetensors",
309
+ "model.layers.39.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
310
+ "model.layers.39.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
311
+ "model.layers.39.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
312
+ "model.layers.39.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
313
+ "model.layers.39.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
314
+ "model.layers.39.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
315
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00005.safetensors",
316
+ "model.layers.4.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
317
+ "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
318
+ "model.layers.4.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
319
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
320
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
321
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
322
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
323
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
324
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00005.safetensors",
325
+ "model.layers.5.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
326
+ "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
327
+ "model.layers.5.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
328
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
329
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
330
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
331
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
332
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
333
+ "model.layers.6.input_layernorm.weight": "model-00002-of-00005.safetensors",
334
+ "model.layers.6.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
335
+ "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
336
+ "model.layers.6.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
337
+ "model.layers.6.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
338
+ "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
339
+ "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
340
+ "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
341
+ "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
342
+ "model.layers.7.input_layernorm.weight": "model-00002-of-00005.safetensors",
343
+ "model.layers.7.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
344
+ "model.layers.7.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
345
+ "model.layers.7.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
346
+ "model.layers.7.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
347
+ "model.layers.7.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
348
+ "model.layers.7.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
349
+ "model.layers.7.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
350
+ "model.layers.7.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
351
+ "model.layers.8.input_layernorm.weight": "model-00002-of-00005.safetensors",
352
+ "model.layers.8.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
353
+ "model.layers.8.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
354
+ "model.layers.8.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
355
+ "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
356
+ "model.layers.8.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
357
+ "model.layers.8.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
358
+ "model.layers.8.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
359
+ "model.layers.8.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
360
+ "model.layers.9.input_layernorm.weight": "model-00002-of-00005.safetensors",
361
+ "model.layers.9.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
362
+ "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
363
+ "model.layers.9.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
364
+ "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
365
+ "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
366
+ "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
367
+ "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
368
+ "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
369
+ "model.norm.weight": "model-00005-of-00005.safetensors"
370
+ }
371
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|im_start|>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|im_end|>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "<|im_end|>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "unk_token": {
24
+ "content": "<unk>",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ }
30
+ }
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:48130f8c042761b84abbfbf10ad07efa7c26108a14e7a2a0402daa06e447a47a
3
+ size 17078668
tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
trainer_state.json ADDED
@@ -0,0 +1,2034 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 0.13614703880190607,
6
+ "eval_steps": 500,
7
+ "global_step": 200,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.0005104645227156713,
14
+ "grad_norm": 24.05441665649414,
15
+ "learning_rate": 0.0,
16
+ "loss": 2.0061,
17
+ "memory/device_reserved (GiB)": 192.97,
18
+ "memory/max_active (GiB)": 139.53,
19
+ "memory/max_allocated (GiB)": 139.53,
20
+ "step": 1
21
+ },
22
+ {
23
+ "epoch": 0.0010209290454313426,
24
+ "grad_norm": 7.6078009605407715,
25
+ "learning_rate": 1.0309278350515465e-07,
26
+ "loss": 1.8967,
27
+ "memory/device_reserved (GiB)": 192.97,
28
+ "memory/max_active (GiB)": 151.03,
29
+ "memory/max_allocated (GiB)": 151.03,
30
+ "step": 2
31
+ },
32
+ {
33
+ "epoch": 0.0015313935681470138,
34
+ "grad_norm": 8.540678977966309,
35
+ "learning_rate": 2.061855670103093e-07,
36
+ "loss": 1.7939,
37
+ "memory/device_reserved (GiB)": 192.97,
38
+ "memory/max_active (GiB)": 151.03,
39
+ "memory/max_allocated (GiB)": 151.03,
40
+ "step": 3
41
+ },
42
+ {
43
+ "epoch": 0.002041858090862685,
44
+ "grad_norm": 16.590530395507812,
45
+ "learning_rate": 3.0927835051546394e-07,
46
+ "loss": 1.9599,
47
+ "memory/device_reserved (GiB)": 192.97,
48
+ "memory/max_active (GiB)": 151.03,
49
+ "memory/max_allocated (GiB)": 151.03,
50
+ "step": 4
51
+ },
52
+ {
53
+ "epoch": 0.002552322613578356,
54
+ "grad_norm": 7.192079544067383,
55
+ "learning_rate": 4.123711340206186e-07,
56
+ "loss": 1.8068,
57
+ "memory/device_reserved (GiB)": 192.97,
58
+ "memory/max_active (GiB)": 151.03,
59
+ "memory/max_allocated (GiB)": 151.03,
60
+ "step": 5
61
+ },
62
+ {
63
+ "epoch": 0.0030627871362940277,
64
+ "grad_norm": 8.165936470031738,
65
+ "learning_rate": 5.154639175257732e-07,
66
+ "loss": 1.8497,
67
+ "memory/device_reserved (GiB)": 192.97,
68
+ "memory/max_active (GiB)": 151.03,
69
+ "memory/max_allocated (GiB)": 151.03,
70
+ "step": 6
71
+ },
72
+ {
73
+ "epoch": 0.0035732516590096988,
74
+ "grad_norm": 8.299514770507812,
75
+ "learning_rate": 6.185567010309279e-07,
76
+ "loss": 1.7926,
77
+ "memory/device_reserved (GiB)": 192.97,
78
+ "memory/max_active (GiB)": 151.03,
79
+ "memory/max_allocated (GiB)": 151.03,
80
+ "step": 7
81
+ },
82
+ {
83
+ "epoch": 0.00408371618172537,
84
+ "grad_norm": 6.091303825378418,
85
+ "learning_rate": 7.216494845360824e-07,
86
+ "loss": 1.8695,
87
+ "memory/device_reserved (GiB)": 192.97,
88
+ "memory/max_active (GiB)": 151.03,
89
+ "memory/max_allocated (GiB)": 151.03,
90
+ "step": 8
91
+ },
92
+ {
93
+ "epoch": 0.004594180704441042,
94
+ "grad_norm": 16.246517181396484,
95
+ "learning_rate": 8.247422680412372e-07,
96
+ "loss": 1.9153,
97
+ "memory/device_reserved (GiB)": 192.97,
98
+ "memory/max_active (GiB)": 151.03,
99
+ "memory/max_allocated (GiB)": 151.03,
100
+ "step": 9
101
+ },
102
+ {
103
+ "epoch": 0.005104645227156712,
104
+ "grad_norm": 7.1781325340271,
105
+ "learning_rate": 9.278350515463919e-07,
106
+ "loss": 1.7798,
107
+ "memory/device_reserved (GiB)": 192.97,
108
+ "memory/max_active (GiB)": 151.03,
109
+ "memory/max_allocated (GiB)": 151.03,
110
+ "step": 10
111
+ },
112
+ {
113
+ "epoch": 0.005615109749872384,
114
+ "grad_norm": 2.5561985969543457,
115
+ "learning_rate": 1.0309278350515464e-06,
116
+ "loss": 1.8484,
117
+ "memory/device_reserved (GiB)": 192.97,
118
+ "memory/max_active (GiB)": 151.03,
119
+ "memory/max_allocated (GiB)": 151.03,
120
+ "step": 11
121
+ },
122
+ {
123
+ "epoch": 0.006125574272588055,
124
+ "grad_norm": 2.5366039276123047,
125
+ "learning_rate": 1.134020618556701e-06,
126
+ "loss": 1.8163,
127
+ "memory/device_reserved (GiB)": 192.97,
128
+ "memory/max_active (GiB)": 151.03,
129
+ "memory/max_allocated (GiB)": 151.03,
130
+ "step": 12
131
+ },
132
+ {
133
+ "epoch": 0.006636038795303726,
134
+ "grad_norm": 2.0043585300445557,
135
+ "learning_rate": 1.2371134020618557e-06,
136
+ "loss": 1.8295,
137
+ "memory/device_reserved (GiB)": 192.97,
138
+ "memory/max_active (GiB)": 151.03,
139
+ "memory/max_allocated (GiB)": 151.03,
140
+ "step": 13
141
+ },
142
+ {
143
+ "epoch": 0.0071465033180193975,
144
+ "grad_norm": 1.26850426197052,
145
+ "learning_rate": 1.3402061855670104e-06,
146
+ "loss": 1.8045,
147
+ "memory/device_reserved (GiB)": 192.97,
148
+ "memory/max_active (GiB)": 151.03,
149
+ "memory/max_allocated (GiB)": 151.03,
150
+ "step": 14
151
+ },
152
+ {
153
+ "epoch": 0.007656967840735069,
154
+ "grad_norm": 1.0957386493682861,
155
+ "learning_rate": 1.4432989690721649e-06,
156
+ "loss": 1.7863,
157
+ "memory/device_reserved (GiB)": 192.97,
158
+ "memory/max_active (GiB)": 151.03,
159
+ "memory/max_allocated (GiB)": 151.03,
160
+ "step": 15
161
+ },
162
+ {
163
+ "epoch": 0.00816743236345074,
164
+ "grad_norm": 1.302420735359192,
165
+ "learning_rate": 1.5463917525773197e-06,
166
+ "loss": 1.7876,
167
+ "memory/device_reserved (GiB)": 192.97,
168
+ "memory/max_active (GiB)": 151.03,
169
+ "memory/max_allocated (GiB)": 151.03,
170
+ "step": 16
171
+ },
172
+ {
173
+ "epoch": 0.008677896886166412,
174
+ "grad_norm": 0.9507644176483154,
175
+ "learning_rate": 1.6494845360824744e-06,
176
+ "loss": 1.7966,
177
+ "memory/device_reserved (GiB)": 192.97,
178
+ "memory/max_active (GiB)": 151.03,
179
+ "memory/max_allocated (GiB)": 151.03,
180
+ "step": 17
181
+ },
182
+ {
183
+ "epoch": 0.009188361408882083,
184
+ "grad_norm": 1.1378878355026245,
185
+ "learning_rate": 1.7525773195876288e-06,
186
+ "loss": 1.8161,
187
+ "memory/device_reserved (GiB)": 192.97,
188
+ "memory/max_active (GiB)": 151.03,
189
+ "memory/max_allocated (GiB)": 151.03,
190
+ "step": 18
191
+ },
192
+ {
193
+ "epoch": 0.009698825931597753,
194
+ "grad_norm": 1.7316354513168335,
195
+ "learning_rate": 1.8556701030927837e-06,
196
+ "loss": 1.7439,
197
+ "memory/device_reserved (GiB)": 192.97,
198
+ "memory/max_active (GiB)": 151.03,
199
+ "memory/max_allocated (GiB)": 151.03,
200
+ "step": 19
201
+ },
202
+ {
203
+ "epoch": 0.010209290454313425,
204
+ "grad_norm": 1.0558087825775146,
205
+ "learning_rate": 1.9587628865979384e-06,
206
+ "loss": 1.7623,
207
+ "memory/device_reserved (GiB)": 192.97,
208
+ "memory/max_active (GiB)": 151.03,
209
+ "memory/max_allocated (GiB)": 151.03,
210
+ "step": 20
211
+ },
212
+ {
213
+ "epoch": 0.010719754977029096,
214
+ "grad_norm": 0.9555009603500366,
215
+ "learning_rate": 2.061855670103093e-06,
216
+ "loss": 1.6405,
217
+ "memory/device_reserved (GiB)": 192.97,
218
+ "memory/max_active (GiB)": 151.03,
219
+ "memory/max_allocated (GiB)": 151.03,
220
+ "step": 21
221
+ },
222
+ {
223
+ "epoch": 0.011230219499744768,
224
+ "grad_norm": 1.0347907543182373,
225
+ "learning_rate": 2.1649484536082477e-06,
226
+ "loss": 1.7348,
227
+ "memory/device_reserved (GiB)": 192.97,
228
+ "memory/max_active (GiB)": 151.03,
229
+ "memory/max_allocated (GiB)": 151.03,
230
+ "step": 22
231
+ },
232
+ {
233
+ "epoch": 0.01174068402246044,
234
+ "grad_norm": 1.1328850984573364,
235
+ "learning_rate": 2.268041237113402e-06,
236
+ "loss": 1.847,
237
+ "memory/device_reserved (GiB)": 192.97,
238
+ "memory/max_active (GiB)": 151.03,
239
+ "memory/max_allocated (GiB)": 151.03,
240
+ "step": 23
241
+ },
242
+ {
243
+ "epoch": 0.01225114854517611,
244
+ "grad_norm": 1.0314826965332031,
245
+ "learning_rate": 2.3711340206185566e-06,
246
+ "loss": 1.7493,
247
+ "memory/device_reserved (GiB)": 192.97,
248
+ "memory/max_active (GiB)": 151.03,
249
+ "memory/max_allocated (GiB)": 151.03,
250
+ "step": 24
251
+ },
252
+ {
253
+ "epoch": 0.012761613067891782,
254
+ "grad_norm": 1.158893346786499,
255
+ "learning_rate": 2.4742268041237115e-06,
256
+ "loss": 1.7491,
257
+ "memory/device_reserved (GiB)": 192.97,
258
+ "memory/max_active (GiB)": 151.03,
259
+ "memory/max_allocated (GiB)": 151.03,
260
+ "step": 25
261
+ },
262
+ {
263
+ "epoch": 0.013272077590607452,
264
+ "grad_norm": 1.144657015800476,
265
+ "learning_rate": 2.577319587628866e-06,
266
+ "loss": 1.8281,
267
+ "memory/device_reserved (GiB)": 192.97,
268
+ "memory/max_active (GiB)": 151.03,
269
+ "memory/max_allocated (GiB)": 151.03,
270
+ "step": 26
271
+ },
272
+ {
273
+ "epoch": 0.013782542113323124,
274
+ "grad_norm": 0.9864128828048706,
275
+ "learning_rate": 2.680412371134021e-06,
276
+ "loss": 1.7979,
277
+ "memory/device_reserved (GiB)": 192.97,
278
+ "memory/max_active (GiB)": 151.03,
279
+ "memory/max_allocated (GiB)": 151.03,
280
+ "step": 27
281
+ },
282
+ {
283
+ "epoch": 0.014293006636038795,
284
+ "grad_norm": 0.9023644328117371,
285
+ "learning_rate": 2.7835051546391757e-06,
286
+ "loss": 1.7567,
287
+ "memory/device_reserved (GiB)": 192.97,
288
+ "memory/max_active (GiB)": 151.03,
289
+ "memory/max_allocated (GiB)": 151.03,
290
+ "step": 28
291
+ },
292
+ {
293
+ "epoch": 0.014803471158754467,
294
+ "grad_norm": 1.0202115774154663,
295
+ "learning_rate": 2.8865979381443297e-06,
296
+ "loss": 1.7217,
297
+ "memory/device_reserved (GiB)": 192.97,
298
+ "memory/max_active (GiB)": 151.03,
299
+ "memory/max_allocated (GiB)": 151.03,
300
+ "step": 29
301
+ },
302
+ {
303
+ "epoch": 0.015313935681470138,
304
+ "grad_norm": 1.4286682605743408,
305
+ "learning_rate": 2.9896907216494846e-06,
306
+ "loss": 1.7248,
307
+ "memory/device_reserved (GiB)": 192.97,
308
+ "memory/max_active (GiB)": 151.03,
309
+ "memory/max_allocated (GiB)": 151.03,
310
+ "step": 30
311
+ },
312
+ {
313
+ "epoch": 0.01582440020418581,
314
+ "grad_norm": 0.8136070966720581,
315
+ "learning_rate": 3.0927835051546395e-06,
316
+ "loss": 1.6771,
317
+ "memory/device_reserved (GiB)": 192.97,
318
+ "memory/max_active (GiB)": 151.03,
319
+ "memory/max_allocated (GiB)": 151.03,
320
+ "step": 31
321
+ },
322
+ {
323
+ "epoch": 0.01633486472690148,
324
+ "grad_norm": 0.9729646444320679,
325
+ "learning_rate": 3.195876288659794e-06,
326
+ "loss": 1.7832,
327
+ "memory/device_reserved (GiB)": 192.97,
328
+ "memory/max_active (GiB)": 151.03,
329
+ "memory/max_allocated (GiB)": 151.03,
330
+ "step": 32
331
+ },
332
+ {
333
+ "epoch": 0.016845329249617153,
334
+ "grad_norm": 1.1746621131896973,
335
+ "learning_rate": 3.298969072164949e-06,
336
+ "loss": 1.7123,
337
+ "memory/device_reserved (GiB)": 192.97,
338
+ "memory/max_active (GiB)": 151.03,
339
+ "memory/max_allocated (GiB)": 151.03,
340
+ "step": 33
341
+ },
342
+ {
343
+ "epoch": 0.017355793772332824,
344
+ "grad_norm": 0.813364565372467,
345
+ "learning_rate": 3.4020618556701037e-06,
346
+ "loss": 1.7838,
347
+ "memory/device_reserved (GiB)": 192.97,
348
+ "memory/max_active (GiB)": 151.03,
349
+ "memory/max_allocated (GiB)": 151.03,
350
+ "step": 34
351
+ },
352
+ {
353
+ "epoch": 0.017866258295048495,
354
+ "grad_norm": 0.9410524368286133,
355
+ "learning_rate": 3.5051546391752577e-06,
356
+ "loss": 1.7666,
357
+ "memory/device_reserved (GiB)": 192.97,
358
+ "memory/max_active (GiB)": 151.03,
359
+ "memory/max_allocated (GiB)": 151.03,
360
+ "step": 35
361
+ },
362
+ {
363
+ "epoch": 0.018376722817764167,
364
+ "grad_norm": 0.7961885929107666,
365
+ "learning_rate": 3.6082474226804126e-06,
366
+ "loss": 1.7823,
367
+ "memory/device_reserved (GiB)": 192.97,
368
+ "memory/max_active (GiB)": 151.03,
369
+ "memory/max_allocated (GiB)": 151.03,
370
+ "step": 36
371
+ },
372
+ {
373
+ "epoch": 0.018887187340479835,
374
+ "grad_norm": 0.8009322881698608,
375
+ "learning_rate": 3.7113402061855674e-06,
376
+ "loss": 1.7066,
377
+ "memory/device_reserved (GiB)": 192.97,
378
+ "memory/max_active (GiB)": 151.03,
379
+ "memory/max_allocated (GiB)": 151.03,
380
+ "step": 37
381
+ },
382
+ {
383
+ "epoch": 0.019397651863195507,
384
+ "grad_norm": 0.9726182222366333,
385
+ "learning_rate": 3.814432989690722e-06,
386
+ "loss": 1.7448,
387
+ "memory/device_reserved (GiB)": 192.97,
388
+ "memory/max_active (GiB)": 151.03,
389
+ "memory/max_allocated (GiB)": 151.03,
390
+ "step": 38
391
+ },
392
+ {
393
+ "epoch": 0.019908116385911178,
394
+ "grad_norm": 0.9403437972068787,
395
+ "learning_rate": 3.917525773195877e-06,
396
+ "loss": 1.8017,
397
+ "memory/device_reserved (GiB)": 192.97,
398
+ "memory/max_active (GiB)": 151.03,
399
+ "memory/max_allocated (GiB)": 151.03,
400
+ "step": 39
401
+ },
402
+ {
403
+ "epoch": 0.02041858090862685,
404
+ "grad_norm": 0.9949467182159424,
405
+ "learning_rate": 4.020618556701032e-06,
406
+ "loss": 1.6682,
407
+ "memory/device_reserved (GiB)": 192.97,
408
+ "memory/max_active (GiB)": 151.03,
409
+ "memory/max_allocated (GiB)": 151.03,
410
+ "step": 40
411
+ },
412
+ {
413
+ "epoch": 0.02092904543134252,
414
+ "grad_norm": 0.8237268328666687,
415
+ "learning_rate": 4.123711340206186e-06,
416
+ "loss": 1.7786,
417
+ "memory/device_reserved (GiB)": 192.97,
418
+ "memory/max_active (GiB)": 151.03,
419
+ "memory/max_allocated (GiB)": 151.03,
420
+ "step": 41
421
+ },
422
+ {
423
+ "epoch": 0.021439509954058193,
424
+ "grad_norm": 0.774246871471405,
425
+ "learning_rate": 4.2268041237113405e-06,
426
+ "loss": 1.7255,
427
+ "memory/device_reserved (GiB)": 192.97,
428
+ "memory/max_active (GiB)": 151.03,
429
+ "memory/max_allocated (GiB)": 151.03,
430
+ "step": 42
431
+ },
432
+ {
433
+ "epoch": 0.021949974476773864,
434
+ "grad_norm": 1.031959891319275,
435
+ "learning_rate": 4.329896907216495e-06,
436
+ "loss": 1.7181,
437
+ "memory/device_reserved (GiB)": 192.97,
438
+ "memory/max_active (GiB)": 151.03,
439
+ "memory/max_allocated (GiB)": 151.03,
440
+ "step": 43
441
+ },
442
+ {
443
+ "epoch": 0.022460438999489536,
444
+ "grad_norm": 1.1743037700653076,
445
+ "learning_rate": 4.4329896907216494e-06,
446
+ "loss": 1.7398,
447
+ "memory/device_reserved (GiB)": 192.97,
448
+ "memory/max_active (GiB)": 151.03,
449
+ "memory/max_allocated (GiB)": 151.03,
450
+ "step": 44
451
+ },
452
+ {
453
+ "epoch": 0.022970903522205207,
454
+ "grad_norm": 0.8437848091125488,
455
+ "learning_rate": 4.536082474226804e-06,
456
+ "loss": 1.8505,
457
+ "memory/device_reserved (GiB)": 192.97,
458
+ "memory/max_active (GiB)": 151.03,
459
+ "memory/max_allocated (GiB)": 151.03,
460
+ "step": 45
461
+ },
462
+ {
463
+ "epoch": 0.02348136804492088,
464
+ "grad_norm": 0.971718430519104,
465
+ "learning_rate": 4.639175257731959e-06,
466
+ "loss": 1.7237,
467
+ "memory/device_reserved (GiB)": 192.97,
468
+ "memory/max_active (GiB)": 151.03,
469
+ "memory/max_allocated (GiB)": 151.03,
470
+ "step": 46
471
+ },
472
+ {
473
+ "epoch": 0.02399183256763655,
474
+ "grad_norm": 0.9551330208778381,
475
+ "learning_rate": 4.742268041237113e-06,
476
+ "loss": 1.6944,
477
+ "memory/device_reserved (GiB)": 192.97,
478
+ "memory/max_active (GiB)": 151.03,
479
+ "memory/max_allocated (GiB)": 151.03,
480
+ "step": 47
481
+ },
482
+ {
483
+ "epoch": 0.02450229709035222,
484
+ "grad_norm": 1.007398009300232,
485
+ "learning_rate": 4.845360824742268e-06,
486
+ "loss": 1.744,
487
+ "memory/device_reserved (GiB)": 192.97,
488
+ "memory/max_active (GiB)": 151.03,
489
+ "memory/max_allocated (GiB)": 151.03,
490
+ "step": 48
491
+ },
492
+ {
493
+ "epoch": 0.025012761613067893,
494
+ "grad_norm": 0.7662305235862732,
495
+ "learning_rate": 4.948453608247423e-06,
496
+ "loss": 1.684,
497
+ "memory/device_reserved (GiB)": 192.97,
498
+ "memory/max_active (GiB)": 151.03,
499
+ "memory/max_allocated (GiB)": 151.03,
500
+ "step": 49
501
+ },
502
+ {
503
+ "epoch": 0.025523226135783564,
504
+ "grad_norm": 0.8253554105758667,
505
+ "learning_rate": 5.051546391752578e-06,
506
+ "loss": 1.7711,
507
+ "memory/device_reserved (GiB)": 192.97,
508
+ "memory/max_active (GiB)": 151.03,
509
+ "memory/max_allocated (GiB)": 151.03,
510
+ "step": 50
511
+ },
512
+ {
513
+ "epoch": 0.026033690658499236,
514
+ "grad_norm": 0.8845403790473938,
515
+ "learning_rate": 5.154639175257732e-06,
516
+ "loss": 1.8203,
517
+ "memory/device_reserved (GiB)": 192.97,
518
+ "memory/max_active (GiB)": 151.03,
519
+ "memory/max_allocated (GiB)": 151.03,
520
+ "step": 51
521
+ },
522
+ {
523
+ "epoch": 0.026544155181214904,
524
+ "grad_norm": 0.8738449215888977,
525
+ "learning_rate": 5.257731958762888e-06,
526
+ "loss": 1.6307,
527
+ "memory/device_reserved (GiB)": 192.97,
528
+ "memory/max_active (GiB)": 151.03,
529
+ "memory/max_allocated (GiB)": 151.03,
530
+ "step": 52
531
+ },
532
+ {
533
+ "epoch": 0.027054619703930576,
534
+ "grad_norm": 0.711958646774292,
535
+ "learning_rate": 5.360824742268042e-06,
536
+ "loss": 1.7172,
537
+ "memory/device_reserved (GiB)": 192.97,
538
+ "memory/max_active (GiB)": 151.03,
539
+ "memory/max_allocated (GiB)": 151.03,
540
+ "step": 53
541
+ },
542
+ {
543
+ "epoch": 0.027565084226646247,
544
+ "grad_norm": 0.7549559473991394,
545
+ "learning_rate": 5.463917525773196e-06,
546
+ "loss": 1.755,
547
+ "memory/device_reserved (GiB)": 192.97,
548
+ "memory/max_active (GiB)": 151.03,
549
+ "memory/max_allocated (GiB)": 151.03,
550
+ "step": 54
551
+ },
552
+ {
553
+ "epoch": 0.02807554874936192,
554
+ "grad_norm": 0.7762870192527771,
555
+ "learning_rate": 5.567010309278351e-06,
556
+ "loss": 1.6802,
557
+ "memory/device_reserved (GiB)": 192.97,
558
+ "memory/max_active (GiB)": 151.03,
559
+ "memory/max_allocated (GiB)": 151.03,
560
+ "step": 55
561
+ },
562
+ {
563
+ "epoch": 0.02858601327207759,
564
+ "grad_norm": 0.8023381233215332,
565
+ "learning_rate": 5.670103092783505e-06,
566
+ "loss": 1.698,
567
+ "memory/device_reserved (GiB)": 192.97,
568
+ "memory/max_active (GiB)": 151.03,
569
+ "memory/max_allocated (GiB)": 151.03,
570
+ "step": 56
571
+ },
572
+ {
573
+ "epoch": 0.02909647779479326,
574
+ "grad_norm": 0.865761399269104,
575
+ "learning_rate": 5.7731958762886594e-06,
576
+ "loss": 1.6885,
577
+ "memory/device_reserved (GiB)": 192.97,
578
+ "memory/max_active (GiB)": 151.03,
579
+ "memory/max_allocated (GiB)": 151.03,
580
+ "step": 57
581
+ },
582
+ {
583
+ "epoch": 0.029606942317508933,
584
+ "grad_norm": 1.0811809301376343,
585
+ "learning_rate": 5.876288659793815e-06,
586
+ "loss": 1.6592,
587
+ "memory/device_reserved (GiB)": 192.97,
588
+ "memory/max_active (GiB)": 151.03,
589
+ "memory/max_allocated (GiB)": 151.03,
590
+ "step": 58
591
+ },
592
+ {
593
+ "epoch": 0.030117406840224605,
594
+ "grad_norm": 0.9070002436637878,
595
+ "learning_rate": 5.979381443298969e-06,
596
+ "loss": 1.7564,
597
+ "memory/device_reserved (GiB)": 192.97,
598
+ "memory/max_active (GiB)": 151.03,
599
+ "memory/max_allocated (GiB)": 151.03,
600
+ "step": 59
601
+ },
602
+ {
603
+ "epoch": 0.030627871362940276,
604
+ "grad_norm": 1.04336416721344,
605
+ "learning_rate": 6.082474226804124e-06,
606
+ "loss": 1.7126,
607
+ "memory/device_reserved (GiB)": 192.97,
608
+ "memory/max_active (GiB)": 151.03,
609
+ "memory/max_allocated (GiB)": 151.03,
610
+ "step": 60
611
+ },
612
+ {
613
+ "epoch": 0.031138335885655948,
614
+ "grad_norm": 1.3839117288589478,
615
+ "learning_rate": 6.185567010309279e-06,
616
+ "loss": 1.6491,
617
+ "memory/device_reserved (GiB)": 192.97,
618
+ "memory/max_active (GiB)": 151.03,
619
+ "memory/max_allocated (GiB)": 151.03,
620
+ "step": 61
621
+ },
622
+ {
623
+ "epoch": 0.03164880040837162,
624
+ "grad_norm": 0.7790964841842651,
625
+ "learning_rate": 6.288659793814433e-06,
626
+ "loss": 1.7819,
627
+ "memory/device_reserved (GiB)": 192.97,
628
+ "memory/max_active (GiB)": 151.03,
629
+ "memory/max_allocated (GiB)": 151.03,
630
+ "step": 62
631
+ },
632
+ {
633
+ "epoch": 0.03215926493108729,
634
+ "grad_norm": 1.3247586488723755,
635
+ "learning_rate": 6.391752577319588e-06,
636
+ "loss": 1.7544,
637
+ "memory/device_reserved (GiB)": 192.97,
638
+ "memory/max_active (GiB)": 151.03,
639
+ "memory/max_allocated (GiB)": 151.03,
640
+ "step": 63
641
+ },
642
+ {
643
+ "epoch": 0.03266972945380296,
644
+ "grad_norm": 1.272275686264038,
645
+ "learning_rate": 6.494845360824743e-06,
646
+ "loss": 1.7166,
647
+ "memory/device_reserved (GiB)": 192.97,
648
+ "memory/max_active (GiB)": 151.03,
649
+ "memory/max_allocated (GiB)": 151.03,
650
+ "step": 64
651
+ },
652
+ {
653
+ "epoch": 0.033180193976518634,
654
+ "grad_norm": 1.0625935792922974,
655
+ "learning_rate": 6.597938144329898e-06,
656
+ "loss": 1.8027,
657
+ "memory/device_reserved (GiB)": 192.97,
658
+ "memory/max_active (GiB)": 151.03,
659
+ "memory/max_allocated (GiB)": 151.03,
660
+ "step": 65
661
+ },
662
+ {
663
+ "epoch": 0.033690658499234305,
664
+ "grad_norm": 1.3712449073791504,
665
+ "learning_rate": 6.701030927835052e-06,
666
+ "loss": 1.6856,
667
+ "memory/device_reserved (GiB)": 192.97,
668
+ "memory/max_active (GiB)": 151.03,
669
+ "memory/max_allocated (GiB)": 151.03,
670
+ "step": 66
671
+ },
672
+ {
673
+ "epoch": 0.034201123021949976,
674
+ "grad_norm": 13.220693588256836,
675
+ "learning_rate": 6.804123711340207e-06,
676
+ "loss": 1.8061,
677
+ "memory/device_reserved (GiB)": 192.97,
678
+ "memory/max_active (GiB)": 151.03,
679
+ "memory/max_allocated (GiB)": 151.03,
680
+ "step": 67
681
+ },
682
+ {
683
+ "epoch": 0.03471158754466565,
684
+ "grad_norm": 1.3873469829559326,
685
+ "learning_rate": 6.907216494845361e-06,
686
+ "loss": 1.6946,
687
+ "memory/device_reserved (GiB)": 192.97,
688
+ "memory/max_active (GiB)": 151.03,
689
+ "memory/max_allocated (GiB)": 151.03,
690
+ "step": 68
691
+ },
692
+ {
693
+ "epoch": 0.03522205206738132,
694
+ "grad_norm": 0.8954477310180664,
695
+ "learning_rate": 7.010309278350515e-06,
696
+ "loss": 1.5911,
697
+ "memory/device_reserved (GiB)": 192.97,
698
+ "memory/max_active (GiB)": 151.03,
699
+ "memory/max_allocated (GiB)": 151.03,
700
+ "step": 69
701
+ },
702
+ {
703
+ "epoch": 0.03573251659009699,
704
+ "grad_norm": 1.6247202157974243,
705
+ "learning_rate": 7.113402061855671e-06,
706
+ "loss": 1.6588,
707
+ "memory/device_reserved (GiB)": 192.97,
708
+ "memory/max_active (GiB)": 151.03,
709
+ "memory/max_allocated (GiB)": 151.03,
710
+ "step": 70
711
+ },
712
+ {
713
+ "epoch": 0.03624298111281266,
714
+ "grad_norm": 1.2285557985305786,
715
+ "learning_rate": 7.216494845360825e-06,
716
+ "loss": 1.7729,
717
+ "memory/device_reserved (GiB)": 192.97,
718
+ "memory/max_active (GiB)": 151.03,
719
+ "memory/max_allocated (GiB)": 151.03,
720
+ "step": 71
721
+ },
722
+ {
723
+ "epoch": 0.036753445635528334,
724
+ "grad_norm": 1.0797786712646484,
725
+ "learning_rate": 7.319587628865979e-06,
726
+ "loss": 1.6978,
727
+ "memory/device_reserved (GiB)": 192.97,
728
+ "memory/max_active (GiB)": 151.03,
729
+ "memory/max_allocated (GiB)": 151.03,
730
+ "step": 72
731
+ },
732
+ {
733
+ "epoch": 0.037263910158244005,
734
+ "grad_norm": 1.8204232454299927,
735
+ "learning_rate": 7.422680412371135e-06,
736
+ "loss": 1.6912,
737
+ "memory/device_reserved (GiB)": 192.97,
738
+ "memory/max_active (GiB)": 151.03,
739
+ "memory/max_allocated (GiB)": 151.03,
740
+ "step": 73
741
+ },
742
+ {
743
+ "epoch": 0.03777437468095967,
744
+ "grad_norm": 3.366705894470215,
745
+ "learning_rate": 7.525773195876289e-06,
746
+ "loss": 1.7523,
747
+ "memory/device_reserved (GiB)": 192.97,
748
+ "memory/max_active (GiB)": 151.03,
749
+ "memory/max_allocated (GiB)": 151.03,
750
+ "step": 74
751
+ },
752
+ {
753
+ "epoch": 0.03828483920367534,
754
+ "grad_norm": 1.5358184576034546,
755
+ "learning_rate": 7.628865979381444e-06,
756
+ "loss": 1.7172,
757
+ "memory/device_reserved (GiB)": 192.97,
758
+ "memory/max_active (GiB)": 151.03,
759
+ "memory/max_allocated (GiB)": 151.03,
760
+ "step": 75
761
+ },
762
+ {
763
+ "epoch": 0.03879530372639101,
764
+ "grad_norm": 0.8976320028305054,
765
+ "learning_rate": 7.731958762886599e-06,
766
+ "loss": 1.7073,
767
+ "memory/device_reserved (GiB)": 192.97,
768
+ "memory/max_active (GiB)": 151.03,
769
+ "memory/max_allocated (GiB)": 151.03,
770
+ "step": 76
771
+ },
772
+ {
773
+ "epoch": 0.039305768249106685,
774
+ "grad_norm": 0.8933356404304504,
775
+ "learning_rate": 7.835051546391754e-06,
776
+ "loss": 1.6702,
777
+ "memory/device_reserved (GiB)": 192.97,
778
+ "memory/max_active (GiB)": 151.03,
779
+ "memory/max_allocated (GiB)": 151.03,
780
+ "step": 77
781
+ },
782
+ {
783
+ "epoch": 0.039816232771822356,
784
+ "grad_norm": 1.2677210569381714,
785
+ "learning_rate": 7.938144329896907e-06,
786
+ "loss": 1.7786,
787
+ "memory/device_reserved (GiB)": 192.97,
788
+ "memory/max_active (GiB)": 151.03,
789
+ "memory/max_allocated (GiB)": 151.03,
790
+ "step": 78
791
+ },
792
+ {
793
+ "epoch": 0.04032669729453803,
794
+ "grad_norm": 0.8787310719490051,
795
+ "learning_rate": 8.041237113402063e-06,
796
+ "loss": 1.6648,
797
+ "memory/device_reserved (GiB)": 192.97,
798
+ "memory/max_active (GiB)": 151.03,
799
+ "memory/max_allocated (GiB)": 151.03,
800
+ "step": 79
801
+ },
802
+ {
803
+ "epoch": 0.0408371618172537,
804
+ "grad_norm": 1.032422661781311,
805
+ "learning_rate": 8.144329896907216e-06,
806
+ "loss": 1.7612,
807
+ "memory/device_reserved (GiB)": 192.97,
808
+ "memory/max_active (GiB)": 151.03,
809
+ "memory/max_allocated (GiB)": 151.03,
810
+ "step": 80
811
+ },
812
+ {
813
+ "epoch": 0.04134762633996937,
814
+ "grad_norm": 0.8892786502838135,
815
+ "learning_rate": 8.247422680412371e-06,
816
+ "loss": 1.7551,
817
+ "memory/device_reserved (GiB)": 192.97,
818
+ "memory/max_active (GiB)": 151.03,
819
+ "memory/max_allocated (GiB)": 151.03,
820
+ "step": 81
821
+ },
822
+ {
823
+ "epoch": 0.04185809086268504,
824
+ "grad_norm": 1.0008693933486938,
825
+ "learning_rate": 8.350515463917526e-06,
826
+ "loss": 1.7573,
827
+ "memory/device_reserved (GiB)": 192.97,
828
+ "memory/max_active (GiB)": 151.03,
829
+ "memory/max_allocated (GiB)": 151.03,
830
+ "step": 82
831
+ },
832
+ {
833
+ "epoch": 0.042368555385400714,
834
+ "grad_norm": 0.9513587951660156,
835
+ "learning_rate": 8.453608247422681e-06,
836
+ "loss": 1.7052,
837
+ "memory/device_reserved (GiB)": 192.97,
838
+ "memory/max_active (GiB)": 151.03,
839
+ "memory/max_allocated (GiB)": 151.03,
840
+ "step": 83
841
+ },
842
+ {
843
+ "epoch": 0.042879019908116385,
844
+ "grad_norm": 0.8307821154594421,
845
+ "learning_rate": 8.556701030927836e-06,
846
+ "loss": 1.7634,
847
+ "memory/device_reserved (GiB)": 192.97,
848
+ "memory/max_active (GiB)": 151.03,
849
+ "memory/max_allocated (GiB)": 151.03,
850
+ "step": 84
851
+ },
852
+ {
853
+ "epoch": 0.043389484430832057,
854
+ "grad_norm": 0.8338541388511658,
855
+ "learning_rate": 8.65979381443299e-06,
856
+ "loss": 1.699,
857
+ "memory/device_reserved (GiB)": 192.97,
858
+ "memory/max_active (GiB)": 151.03,
859
+ "memory/max_allocated (GiB)": 151.03,
860
+ "step": 85
861
+ },
862
+ {
863
+ "epoch": 0.04389994895354773,
864
+ "grad_norm": 0.9660134315490723,
865
+ "learning_rate": 8.762886597938146e-06,
866
+ "loss": 1.6446,
867
+ "memory/device_reserved (GiB)": 192.97,
868
+ "memory/max_active (GiB)": 151.03,
869
+ "memory/max_allocated (GiB)": 151.03,
870
+ "step": 86
871
+ },
872
+ {
873
+ "epoch": 0.0444104134762634,
874
+ "grad_norm": 1.0152493715286255,
875
+ "learning_rate": 8.865979381443299e-06,
876
+ "loss": 1.7269,
877
+ "memory/device_reserved (GiB)": 192.97,
878
+ "memory/max_active (GiB)": 151.03,
879
+ "memory/max_allocated (GiB)": 151.03,
880
+ "step": 87
881
+ },
882
+ {
883
+ "epoch": 0.04492087799897907,
884
+ "grad_norm": 1.0614452362060547,
885
+ "learning_rate": 8.969072164948455e-06,
886
+ "loss": 1.6373,
887
+ "memory/device_reserved (GiB)": 192.97,
888
+ "memory/max_active (GiB)": 151.03,
889
+ "memory/max_allocated (GiB)": 151.03,
890
+ "step": 88
891
+ },
892
+ {
893
+ "epoch": 0.04543134252169474,
894
+ "grad_norm": 4.689784526824951,
895
+ "learning_rate": 9.072164948453609e-06,
896
+ "loss": 1.8024,
897
+ "memory/device_reserved (GiB)": 192.97,
898
+ "memory/max_active (GiB)": 151.03,
899
+ "memory/max_allocated (GiB)": 151.03,
900
+ "step": 89
901
+ },
902
+ {
903
+ "epoch": 0.045941807044410414,
904
+ "grad_norm": 2.7629218101501465,
905
+ "learning_rate": 9.175257731958764e-06,
906
+ "loss": 1.7774,
907
+ "memory/device_reserved (GiB)": 192.97,
908
+ "memory/max_active (GiB)": 151.03,
909
+ "memory/max_allocated (GiB)": 151.03,
910
+ "step": 90
911
+ },
912
+ {
913
+ "epoch": 0.046452271567126086,
914
+ "grad_norm": 1.2467944622039795,
915
+ "learning_rate": 9.278350515463918e-06,
916
+ "loss": 1.7005,
917
+ "memory/device_reserved (GiB)": 192.97,
918
+ "memory/max_active (GiB)": 151.03,
919
+ "memory/max_allocated (GiB)": 151.03,
920
+ "step": 91
921
+ },
922
+ {
923
+ "epoch": 0.04696273608984176,
924
+ "grad_norm": 1.175451636314392,
925
+ "learning_rate": 9.381443298969073e-06,
926
+ "loss": 1.708,
927
+ "memory/device_reserved (GiB)": 192.97,
928
+ "memory/max_active (GiB)": 151.03,
929
+ "memory/max_allocated (GiB)": 151.03,
930
+ "step": 92
931
+ },
932
+ {
933
+ "epoch": 0.04747320061255743,
934
+ "grad_norm": 36.13218307495117,
935
+ "learning_rate": 9.484536082474226e-06,
936
+ "loss": 1.9211,
937
+ "memory/device_reserved (GiB)": 192.97,
938
+ "memory/max_active (GiB)": 151.03,
939
+ "memory/max_allocated (GiB)": 151.03,
940
+ "step": 93
941
+ },
942
+ {
943
+ "epoch": 0.0479836651352731,
944
+ "grad_norm": 1.6346375942230225,
945
+ "learning_rate": 9.587628865979383e-06,
946
+ "loss": 1.6819,
947
+ "memory/device_reserved (GiB)": 192.97,
948
+ "memory/max_active (GiB)": 151.03,
949
+ "memory/max_allocated (GiB)": 151.03,
950
+ "step": 94
951
+ },
952
+ {
953
+ "epoch": 0.04849412965798877,
954
+ "grad_norm": 1.2270629405975342,
955
+ "learning_rate": 9.690721649484536e-06,
956
+ "loss": 1.5809,
957
+ "memory/device_reserved (GiB)": 192.97,
958
+ "memory/max_active (GiB)": 151.03,
959
+ "memory/max_allocated (GiB)": 151.03,
960
+ "step": 95
961
+ },
962
+ {
963
+ "epoch": 0.04900459418070444,
964
+ "grad_norm": 1.4751657247543335,
965
+ "learning_rate": 9.793814432989691e-06,
966
+ "loss": 1.7517,
967
+ "memory/device_reserved (GiB)": 192.97,
968
+ "memory/max_active (GiB)": 151.03,
969
+ "memory/max_allocated (GiB)": 151.03,
970
+ "step": 96
971
+ },
972
+ {
973
+ "epoch": 0.049515058703420115,
974
+ "grad_norm": 1.174103856086731,
975
+ "learning_rate": 9.896907216494846e-06,
976
+ "loss": 1.6645,
977
+ "memory/device_reserved (GiB)": 192.97,
978
+ "memory/max_active (GiB)": 151.03,
979
+ "memory/max_allocated (GiB)": 151.03,
980
+ "step": 97
981
+ },
982
+ {
983
+ "epoch": 0.050025523226135786,
984
+ "grad_norm": 1.0809050798416138,
985
+ "learning_rate": 1e-05,
986
+ "loss": 1.7526,
987
+ "memory/device_reserved (GiB)": 192.97,
988
+ "memory/max_active (GiB)": 151.03,
989
+ "memory/max_allocated (GiB)": 151.03,
990
+ "step": 98
991
+ },
992
+ {
993
+ "epoch": 0.05053598774885146,
994
+ "grad_norm": 0.9332408308982849,
995
+ "learning_rate": 9.999992883273144e-06,
996
+ "loss": 1.717,
997
+ "memory/device_reserved (GiB)": 192.97,
998
+ "memory/max_active (GiB)": 151.03,
999
+ "memory/max_allocated (GiB)": 151.03,
1000
+ "step": 99
1001
+ },
1002
+ {
1003
+ "epoch": 0.05104645227156713,
1004
+ "grad_norm": 0.9629523754119873,
1005
+ "learning_rate": 9.999971533112832e-06,
1006
+ "loss": 1.6674,
1007
+ "memory/device_reserved (GiB)": 192.97,
1008
+ "memory/max_active (GiB)": 151.03,
1009
+ "memory/max_allocated (GiB)": 151.03,
1010
+ "step": 100
1011
+ },
1012
+ {
1013
+ "epoch": 0.06875425459496257,
1014
+ "grad_norm": 0.9861069321632385,
1015
+ "learning_rate": 9.999935949579843e-06,
1016
+ "loss": 1.7583,
1017
+ "memory/device_reserved (GiB)": 234.63,
1018
+ "memory/max_active (GiB)": 186.82,
1019
+ "memory/max_allocated (GiB)": 186.82,
1020
+ "step": 101
1021
+ },
1022
+ {
1023
+ "epoch": 0.06943498978897208,
1024
+ "grad_norm": 1.425486445426941,
1025
+ "learning_rate": 9.898346201737316e-06,
1026
+ "loss": 1.7852,
1027
+ "memory/device_reserved (GiB)": 234.63,
1028
+ "memory/max_active (GiB)": 186.82,
1029
+ "memory/max_allocated (GiB)": 186.82,
1030
+ "step": 102
1031
+ },
1032
+ {
1033
+ "epoch": 0.07011572498298162,
1034
+ "grad_norm": 1.648892879486084,
1035
+ "learning_rate": 9.896179406315343e-06,
1036
+ "loss": 1.6976,
1037
+ "memory/device_reserved (GiB)": 234.63,
1038
+ "memory/max_active (GiB)": 186.82,
1039
+ "memory/max_allocated (GiB)": 186.82,
1040
+ "step": 103
1041
+ },
1042
+ {
1043
+ "epoch": 0.07079646017699115,
1044
+ "grad_norm": 1.883970022201538,
1045
+ "learning_rate": 9.893990002892777e-06,
1046
+ "loss": 1.7738,
1047
+ "memory/device_reserved (GiB)": 234.63,
1048
+ "memory/max_active (GiB)": 186.82,
1049
+ "memory/max_allocated (GiB)": 186.82,
1050
+ "step": 104
1051
+ },
1052
+ {
1053
+ "epoch": 0.07147719537100068,
1054
+ "grad_norm": 1.1324390172958374,
1055
+ "learning_rate": 9.891778001579136e-06,
1056
+ "loss": 1.7525,
1057
+ "memory/device_reserved (GiB)": 234.63,
1058
+ "memory/max_active (GiB)": 186.82,
1059
+ "memory/max_allocated (GiB)": 186.82,
1060
+ "step": 105
1061
+ },
1062
+ {
1063
+ "epoch": 0.07215793056501021,
1064
+ "grad_norm": 1.5833842754364014,
1065
+ "learning_rate": 9.88954341258829e-06,
1066
+ "loss": 1.7709,
1067
+ "memory/device_reserved (GiB)": 234.63,
1068
+ "memory/max_active (GiB)": 186.82,
1069
+ "memory/max_allocated (GiB)": 186.82,
1070
+ "step": 106
1071
+ },
1072
+ {
1073
+ "epoch": 0.07283866575901975,
1074
+ "grad_norm": 1.1700878143310547,
1075
+ "learning_rate": 9.887286246238406e-06,
1076
+ "loss": 1.7962,
1077
+ "memory/device_reserved (GiB)": 234.63,
1078
+ "memory/max_active (GiB)": 186.82,
1079
+ "memory/max_allocated (GiB)": 186.82,
1080
+ "step": 107
1081
+ },
1082
+ {
1083
+ "epoch": 0.07351940095302927,
1084
+ "grad_norm": 1.573387861251831,
1085
+ "learning_rate": 9.885006512951898e-06,
1086
+ "loss": 1.7308,
1087
+ "memory/device_reserved (GiB)": 234.63,
1088
+ "memory/max_active (GiB)": 186.82,
1089
+ "memory/max_allocated (GiB)": 186.82,
1090
+ "step": 108
1091
+ },
1092
+ {
1093
+ "epoch": 0.0742001361470388,
1094
+ "grad_norm": 2.2107796669006348,
1095
+ "learning_rate": 9.882704223255383e-06,
1096
+ "loss": 1.7296,
1097
+ "memory/device_reserved (GiB)": 234.63,
1098
+ "memory/max_active (GiB)": 186.82,
1099
+ "memory/max_allocated (GiB)": 186.82,
1100
+ "step": 109
1101
+ },
1102
+ {
1103
+ "epoch": 0.07488087134104833,
1104
+ "grad_norm": 0.7726507186889648,
1105
+ "learning_rate": 9.880379387779637e-06,
1106
+ "loss": 1.7369,
1107
+ "memory/device_reserved (GiB)": 234.63,
1108
+ "memory/max_active (GiB)": 186.82,
1109
+ "memory/max_allocated (GiB)": 186.82,
1110
+ "step": 110
1111
+ },
1112
+ {
1113
+ "epoch": 0.07556160653505786,
1114
+ "grad_norm": 1.3989717960357666,
1115
+ "learning_rate": 9.878032017259533e-06,
1116
+ "loss": 1.7628,
1117
+ "memory/device_reserved (GiB)": 234.63,
1118
+ "memory/max_active (GiB)": 186.82,
1119
+ "memory/max_allocated (GiB)": 186.82,
1120
+ "step": 111
1121
+ },
1122
+ {
1123
+ "epoch": 0.0762423417290674,
1124
+ "grad_norm": 0.7562165260314941,
1125
+ "learning_rate": 9.875662122534004e-06,
1126
+ "loss": 1.6657,
1127
+ "memory/device_reserved (GiB)": 234.63,
1128
+ "memory/max_active (GiB)": 186.82,
1129
+ "memory/max_allocated (GiB)": 186.82,
1130
+ "step": 112
1131
+ },
1132
+ {
1133
+ "epoch": 0.07692307692307693,
1134
+ "grad_norm": 1.1455652713775635,
1135
+ "learning_rate": 9.873269714545986e-06,
1136
+ "loss": 1.7242,
1137
+ "memory/device_reserved (GiB)": 234.63,
1138
+ "memory/max_active (GiB)": 186.82,
1139
+ "memory/max_allocated (GiB)": 186.82,
1140
+ "step": 113
1141
+ },
1142
+ {
1143
+ "epoch": 0.07760381211708646,
1144
+ "grad_norm": 0.7659608721733093,
1145
+ "learning_rate": 9.87085480434237e-06,
1146
+ "loss": 1.6782,
1147
+ "memory/device_reserved (GiB)": 234.63,
1148
+ "memory/max_active (GiB)": 186.82,
1149
+ "memory/max_allocated (GiB)": 186.82,
1150
+ "step": 114
1151
+ },
1152
+ {
1153
+ "epoch": 0.07828454731109598,
1154
+ "grad_norm": 1.2639816999435425,
1155
+ "learning_rate": 9.868417403073954e-06,
1156
+ "loss": 1.7197,
1157
+ "memory/device_reserved (GiB)": 234.63,
1158
+ "memory/max_active (GiB)": 186.82,
1159
+ "memory/max_allocated (GiB)": 186.82,
1160
+ "step": 115
1161
+ },
1162
+ {
1163
+ "epoch": 0.07896528250510551,
1164
+ "grad_norm": 0.8840866088867188,
1165
+ "learning_rate": 9.86595752199538e-06,
1166
+ "loss": 1.7588,
1167
+ "memory/device_reserved (GiB)": 234.63,
1168
+ "memory/max_active (GiB)": 186.82,
1169
+ "memory/max_allocated (GiB)": 186.82,
1170
+ "step": 116
1171
+ },
1172
+ {
1173
+ "epoch": 0.07964601769911504,
1174
+ "grad_norm": 0.9605395793914795,
1175
+ "learning_rate": 9.863475172465096e-06,
1176
+ "loss": 1.746,
1177
+ "memory/device_reserved (GiB)": 234.63,
1178
+ "memory/max_active (GiB)": 186.82,
1179
+ "memory/max_allocated (GiB)": 186.82,
1180
+ "step": 117
1181
+ },
1182
+ {
1183
+ "epoch": 0.08032675289312458,
1184
+ "grad_norm": 1.208536148071289,
1185
+ "learning_rate": 9.8609703659453e-06,
1186
+ "loss": 1.8172,
1187
+ "memory/device_reserved (GiB)": 234.63,
1188
+ "memory/max_active (GiB)": 186.82,
1189
+ "memory/max_allocated (GiB)": 186.82,
1190
+ "step": 118
1191
+ },
1192
+ {
1193
+ "epoch": 0.08100748808713411,
1194
+ "grad_norm": 0.9458699226379395,
1195
+ "learning_rate": 9.858443114001876e-06,
1196
+ "loss": 1.6307,
1197
+ "memory/device_reserved (GiB)": 234.63,
1198
+ "memory/max_active (GiB)": 186.82,
1199
+ "memory/max_allocated (GiB)": 186.82,
1200
+ "step": 119
1201
+ },
1202
+ {
1203
+ "epoch": 0.08168822328114364,
1204
+ "grad_norm": 6.640661239624023,
1205
+ "learning_rate": 9.855893428304357e-06,
1206
+ "loss": 1.7085,
1207
+ "memory/device_reserved (GiB)": 234.63,
1208
+ "memory/max_active (GiB)": 186.82,
1209
+ "memory/max_allocated (GiB)": 186.82,
1210
+ "step": 120
1211
+ },
1212
+ {
1213
+ "epoch": 0.08236895847515316,
1214
+ "grad_norm": 4.13405704498291,
1215
+ "learning_rate": 9.853321320625859e-06,
1216
+ "loss": 1.7143,
1217
+ "memory/device_reserved (GiB)": 234.63,
1218
+ "memory/max_active (GiB)": 186.82,
1219
+ "memory/max_allocated (GiB)": 186.82,
1220
+ "step": 121
1221
+ },
1222
+ {
1223
+ "epoch": 0.08304969366916269,
1224
+ "grad_norm": 1.9490628242492676,
1225
+ "learning_rate": 9.850726802843035e-06,
1226
+ "loss": 1.7832,
1227
+ "memory/device_reserved (GiB)": 234.63,
1228
+ "memory/max_active (GiB)": 186.82,
1229
+ "memory/max_allocated (GiB)": 186.82,
1230
+ "step": 122
1231
+ },
1232
+ {
1233
+ "epoch": 0.08373042886317222,
1234
+ "grad_norm": 0.9990502595901489,
1235
+ "learning_rate": 9.848109886936011e-06,
1236
+ "loss": 1.6934,
1237
+ "memory/device_reserved (GiB)": 234.63,
1238
+ "memory/max_active (GiB)": 186.82,
1239
+ "memory/max_allocated (GiB)": 186.82,
1240
+ "step": 123
1241
+ },
1242
+ {
1243
+ "epoch": 0.08441116405718176,
1244
+ "grad_norm": 1.1732097864151,
1245
+ "learning_rate": 9.84547058498834e-06,
1246
+ "loss": 1.7131,
1247
+ "memory/device_reserved (GiB)": 234.63,
1248
+ "memory/max_active (GiB)": 186.82,
1249
+ "memory/max_allocated (GiB)": 186.82,
1250
+ "step": 124
1251
+ },
1252
+ {
1253
+ "epoch": 0.08509189925119129,
1254
+ "grad_norm": 0.9427511692047119,
1255
+ "learning_rate": 9.842808909186941e-06,
1256
+ "loss": 1.73,
1257
+ "memory/device_reserved (GiB)": 234.63,
1258
+ "memory/max_active (GiB)": 186.82,
1259
+ "memory/max_allocated (GiB)": 186.82,
1260
+ "step": 125
1261
+ },
1262
+ {
1263
+ "epoch": 0.08577263444520082,
1264
+ "grad_norm": 1.0290261507034302,
1265
+ "learning_rate": 9.84012487182204e-06,
1266
+ "loss": 1.7099,
1267
+ "memory/device_reserved (GiB)": 234.63,
1268
+ "memory/max_active (GiB)": 186.82,
1269
+ "memory/max_allocated (GiB)": 186.82,
1270
+ "step": 126
1271
+ },
1272
+ {
1273
+ "epoch": 0.08645336963921035,
1274
+ "grad_norm": 0.9603204727172852,
1275
+ "learning_rate": 9.837418485287126e-06,
1276
+ "loss": 1.7028,
1277
+ "memory/device_reserved (GiB)": 234.63,
1278
+ "memory/max_active (GiB)": 186.82,
1279
+ "memory/max_allocated (GiB)": 186.82,
1280
+ "step": 127
1281
+ },
1282
+ {
1283
+ "epoch": 0.08713410483321987,
1284
+ "grad_norm": 1.0807061195373535,
1285
+ "learning_rate": 9.834689762078877e-06,
1286
+ "loss": 1.6857,
1287
+ "memory/device_reserved (GiB)": 234.63,
1288
+ "memory/max_active (GiB)": 186.82,
1289
+ "memory/max_allocated (GiB)": 186.82,
1290
+ "step": 128
1291
+ },
1292
+ {
1293
+ "epoch": 0.0878148400272294,
1294
+ "grad_norm": 1.2012745141983032,
1295
+ "learning_rate": 9.83193871479711e-06,
1296
+ "loss": 1.7612,
1297
+ "memory/device_reserved (GiB)": 234.63,
1298
+ "memory/max_active (GiB)": 186.82,
1299
+ "memory/max_allocated (GiB)": 186.82,
1300
+ "step": 129
1301
+ },
1302
+ {
1303
+ "epoch": 0.08849557522123894,
1304
+ "grad_norm": 1.2601819038391113,
1305
+ "learning_rate": 9.829165356144728e-06,
1306
+ "loss": 1.7485,
1307
+ "memory/device_reserved (GiB)": 234.63,
1308
+ "memory/max_active (GiB)": 186.82,
1309
+ "memory/max_allocated (GiB)": 186.82,
1310
+ "step": 130
1311
+ },
1312
+ {
1313
+ "epoch": 0.08917631041524847,
1314
+ "grad_norm": 0.7284013628959656,
1315
+ "learning_rate": 9.82636969892765e-06,
1316
+ "loss": 1.7126,
1317
+ "memory/device_reserved (GiB)": 234.63,
1318
+ "memory/max_active (GiB)": 186.82,
1319
+ "memory/max_allocated (GiB)": 186.82,
1320
+ "step": 131
1321
+ },
1322
+ {
1323
+ "epoch": 0.089857045609258,
1324
+ "grad_norm": 1.1513925790786743,
1325
+ "learning_rate": 9.823551756054768e-06,
1326
+ "loss": 1.7005,
1327
+ "memory/device_reserved (GiB)": 234.63,
1328
+ "memory/max_active (GiB)": 186.82,
1329
+ "memory/max_allocated (GiB)": 186.82,
1330
+ "step": 132
1331
+ },
1332
+ {
1333
+ "epoch": 0.09053778080326753,
1334
+ "grad_norm": 0.660559356212616,
1335
+ "learning_rate": 9.820711540537866e-06,
1336
+ "loss": 1.6811,
1337
+ "memory/device_reserved (GiB)": 234.63,
1338
+ "memory/max_active (GiB)": 186.82,
1339
+ "memory/max_allocated (GiB)": 186.82,
1340
+ "step": 133
1341
+ },
1342
+ {
1343
+ "epoch": 0.09121851599727705,
1344
+ "grad_norm": 1.0490988492965698,
1345
+ "learning_rate": 9.817849065491576e-06,
1346
+ "loss": 1.7433,
1347
+ "memory/device_reserved (GiB)": 234.63,
1348
+ "memory/max_active (GiB)": 186.82,
1349
+ "memory/max_allocated (GiB)": 186.82,
1350
+ "step": 134
1351
+ },
1352
+ {
1353
+ "epoch": 0.09189925119128659,
1354
+ "grad_norm": 0.8521629571914673,
1355
+ "learning_rate": 9.814964344133318e-06,
1356
+ "loss": 1.7245,
1357
+ "memory/device_reserved (GiB)": 234.63,
1358
+ "memory/max_active (GiB)": 186.82,
1359
+ "memory/max_allocated (GiB)": 186.82,
1360
+ "step": 135
1361
+ },
1362
+ {
1363
+ "epoch": 0.09257998638529612,
1364
+ "grad_norm": 0.8048623204231262,
1365
+ "learning_rate": 9.812057389783225e-06,
1366
+ "loss": 1.7915,
1367
+ "memory/device_reserved (GiB)": 234.63,
1368
+ "memory/max_active (GiB)": 186.82,
1369
+ "memory/max_allocated (GiB)": 186.82,
1370
+ "step": 136
1371
+ },
1372
+ {
1373
+ "epoch": 0.09326072157930565,
1374
+ "grad_norm": 0.8406012654304504,
1375
+ "learning_rate": 9.809128215864096e-06,
1376
+ "loss": 1.7127,
1377
+ "memory/device_reserved (GiB)": 234.63,
1378
+ "memory/max_active (GiB)": 186.82,
1379
+ "memory/max_allocated (GiB)": 186.82,
1380
+ "step": 137
1381
+ },
1382
+ {
1383
+ "epoch": 0.09394145677331518,
1384
+ "grad_norm": 1.0638079643249512,
1385
+ "learning_rate": 9.806176835901329e-06,
1386
+ "loss": 1.6889,
1387
+ "memory/device_reserved (GiB)": 234.63,
1388
+ "memory/max_active (GiB)": 186.82,
1389
+ "memory/max_allocated (GiB)": 186.82,
1390
+ "step": 138
1391
+ },
1392
+ {
1393
+ "epoch": 0.09462219196732471,
1394
+ "grad_norm": 0.8079673647880554,
1395
+ "learning_rate": 9.803203263522854e-06,
1396
+ "loss": 1.7144,
1397
+ "memory/device_reserved (GiB)": 234.63,
1398
+ "memory/max_active (GiB)": 186.82,
1399
+ "memory/max_allocated (GiB)": 186.82,
1400
+ "step": 139
1401
+ },
1402
+ {
1403
+ "epoch": 0.09530292716133425,
1404
+ "grad_norm": 0.6343026161193848,
1405
+ "learning_rate": 9.800207512459076e-06,
1406
+ "loss": 1.6674,
1407
+ "memory/device_reserved (GiB)": 234.63,
1408
+ "memory/max_active (GiB)": 186.82,
1409
+ "memory/max_allocated (GiB)": 186.82,
1410
+ "step": 140
1411
+ },
1412
+ {
1413
+ "epoch": 0.09598366235534377,
1414
+ "grad_norm": 0.8282296657562256,
1415
+ "learning_rate": 9.797189596542809e-06,
1416
+ "loss": 1.6704,
1417
+ "memory/device_reserved (GiB)": 234.63,
1418
+ "memory/max_active (GiB)": 186.82,
1419
+ "memory/max_allocated (GiB)": 186.82,
1420
+ "step": 141
1421
+ },
1422
+ {
1423
+ "epoch": 0.0966643975493533,
1424
+ "grad_norm": 0.7079451084136963,
1425
+ "learning_rate": 9.794149529709217e-06,
1426
+ "loss": 1.7305,
1427
+ "memory/device_reserved (GiB)": 234.63,
1428
+ "memory/max_active (GiB)": 186.82,
1429
+ "memory/max_allocated (GiB)": 186.82,
1430
+ "step": 142
1431
+ },
1432
+ {
1433
+ "epoch": 0.09734513274336283,
1434
+ "grad_norm": 0.6755410432815552,
1435
+ "learning_rate": 9.791087325995737e-06,
1436
+ "loss": 1.6668,
1437
+ "memory/device_reserved (GiB)": 234.63,
1438
+ "memory/max_active (GiB)": 186.82,
1439
+ "memory/max_allocated (GiB)": 186.82,
1440
+ "step": 143
1441
+ },
1442
+ {
1443
+ "epoch": 0.09802586793737236,
1444
+ "grad_norm": 1.338319182395935,
1445
+ "learning_rate": 9.78800299954203e-06,
1446
+ "loss": 1.674,
1447
+ "memory/device_reserved (GiB)": 234.63,
1448
+ "memory/max_active (GiB)": 186.82,
1449
+ "memory/max_allocated (GiB)": 186.82,
1450
+ "step": 144
1451
+ },
1452
+ {
1453
+ "epoch": 0.0987066031313819,
1454
+ "grad_norm": 0.8062757253646851,
1455
+ "learning_rate": 9.784896564589905e-06,
1456
+ "loss": 1.6971,
1457
+ "memory/device_reserved (GiB)": 234.63,
1458
+ "memory/max_active (GiB)": 186.82,
1459
+ "memory/max_allocated (GiB)": 186.82,
1460
+ "step": 145
1461
+ },
1462
+ {
1463
+ "epoch": 0.09938733832539143,
1464
+ "grad_norm": 0.7266926169395447,
1465
+ "learning_rate": 9.781768035483256e-06,
1466
+ "loss": 1.7531,
1467
+ "memory/device_reserved (GiB)": 234.63,
1468
+ "memory/max_active (GiB)": 186.82,
1469
+ "memory/max_allocated (GiB)": 186.82,
1470
+ "step": 146
1471
+ },
1472
+ {
1473
+ "epoch": 0.10006807351940095,
1474
+ "grad_norm": 0.946113109588623,
1475
+ "learning_rate": 9.778617426667998e-06,
1476
+ "loss": 1.7512,
1477
+ "memory/device_reserved (GiB)": 234.63,
1478
+ "memory/max_active (GiB)": 186.82,
1479
+ "memory/max_allocated (GiB)": 186.82,
1480
+ "step": 147
1481
+ },
1482
+ {
1483
+ "epoch": 0.10074880871341048,
1484
+ "grad_norm": 0.7514466643333435,
1485
+ "learning_rate": 9.775444752691998e-06,
1486
+ "loss": 1.6771,
1487
+ "memory/device_reserved (GiB)": 234.63,
1488
+ "memory/max_active (GiB)": 186.82,
1489
+ "memory/max_allocated (GiB)": 186.82,
1490
+ "step": 148
1491
+ },
1492
+ {
1493
+ "epoch": 0.10142954390742001,
1494
+ "grad_norm": 1.0235679149627686,
1495
+ "learning_rate": 9.772250028205009e-06,
1496
+ "loss": 1.6477,
1497
+ "memory/device_reserved (GiB)": 234.63,
1498
+ "memory/max_active (GiB)": 186.82,
1499
+ "memory/max_allocated (GiB)": 186.82,
1500
+ "step": 149
1501
+ },
1502
+ {
1503
+ "epoch": 0.10211027910142954,
1504
+ "grad_norm": 0.7400968074798584,
1505
+ "learning_rate": 9.769033267958598e-06,
1506
+ "loss": 1.7386,
1507
+ "memory/device_reserved (GiB)": 234.63,
1508
+ "memory/max_active (GiB)": 186.82,
1509
+ "memory/max_allocated (GiB)": 186.82,
1510
+ "step": 150
1511
+ },
1512
+ {
1513
+ "epoch": 0.10279101429543908,
1514
+ "grad_norm": 0.8439730405807495,
1515
+ "learning_rate": 9.765794486806089e-06,
1516
+ "loss": 1.6702,
1517
+ "memory/device_reserved (GiB)": 234.63,
1518
+ "memory/max_active (GiB)": 186.82,
1519
+ "memory/max_allocated (GiB)": 186.82,
1520
+ "step": 151
1521
+ },
1522
+ {
1523
+ "epoch": 0.10347174948944861,
1524
+ "grad_norm": 0.9278808236122131,
1525
+ "learning_rate": 9.76253369970248e-06,
1526
+ "loss": 1.756,
1527
+ "memory/device_reserved (GiB)": 234.63,
1528
+ "memory/max_active (GiB)": 186.82,
1529
+ "memory/max_allocated (GiB)": 186.82,
1530
+ "step": 152
1531
+ },
1532
+ {
1533
+ "epoch": 0.10415248468345814,
1534
+ "grad_norm": 0.7247333526611328,
1535
+ "learning_rate": 9.759250921704382e-06,
1536
+ "loss": 1.7133,
1537
+ "memory/device_reserved (GiB)": 234.63,
1538
+ "memory/max_active (GiB)": 186.82,
1539
+ "memory/max_allocated (GiB)": 186.82,
1540
+ "step": 153
1541
+ },
1542
+ {
1543
+ "epoch": 0.10483321987746766,
1544
+ "grad_norm": 0.7844570279121399,
1545
+ "learning_rate": 9.755946167969952e-06,
1546
+ "loss": 1.6426,
1547
+ "memory/device_reserved (GiB)": 234.63,
1548
+ "memory/max_active (GiB)": 186.82,
1549
+ "memory/max_allocated (GiB)": 186.82,
1550
+ "step": 154
1551
+ },
1552
+ {
1553
+ "epoch": 0.10551395507147719,
1554
+ "grad_norm": 0.878671407699585,
1555
+ "learning_rate": 9.752619453758818e-06,
1556
+ "loss": 1.7451,
1557
+ "memory/device_reserved (GiB)": 234.63,
1558
+ "memory/max_active (GiB)": 186.82,
1559
+ "memory/max_allocated (GiB)": 186.82,
1560
+ "step": 155
1561
+ },
1562
+ {
1563
+ "epoch": 0.10619469026548672,
1564
+ "grad_norm": 0.8259819149971008,
1565
+ "learning_rate": 9.749270794432011e-06,
1566
+ "loss": 1.7338,
1567
+ "memory/device_reserved (GiB)": 234.63,
1568
+ "memory/max_active (GiB)": 186.82,
1569
+ "memory/max_allocated (GiB)": 186.82,
1570
+ "step": 156
1571
+ },
1572
+ {
1573
+ "epoch": 0.10687542545949626,
1574
+ "grad_norm": 1.142391324043274,
1575
+ "learning_rate": 9.745900205451888e-06,
1576
+ "loss": 1.6637,
1577
+ "memory/device_reserved (GiB)": 234.63,
1578
+ "memory/max_active (GiB)": 186.82,
1579
+ "memory/max_allocated (GiB)": 186.82,
1580
+ "step": 157
1581
+ },
1582
+ {
1583
+ "epoch": 0.10755616065350579,
1584
+ "grad_norm": 0.8899725079536438,
1585
+ "learning_rate": 9.74250770238207e-06,
1586
+ "loss": 1.6494,
1587
+ "memory/device_reserved (GiB)": 234.63,
1588
+ "memory/max_active (GiB)": 186.82,
1589
+ "memory/max_allocated (GiB)": 186.82,
1590
+ "step": 158
1591
+ },
1592
+ {
1593
+ "epoch": 0.10823689584751532,
1594
+ "grad_norm": 0.7415008544921875,
1595
+ "learning_rate": 9.73909330088737e-06,
1596
+ "loss": 1.6499,
1597
+ "memory/device_reserved (GiB)": 234.63,
1598
+ "memory/max_active (GiB)": 186.82,
1599
+ "memory/max_allocated (GiB)": 186.82,
1600
+ "step": 159
1601
+ },
1602
+ {
1603
+ "epoch": 0.10891763104152484,
1604
+ "grad_norm": 0.7182707786560059,
1605
+ "learning_rate": 9.735657016733706e-06,
1606
+ "loss": 1.7394,
1607
+ "memory/device_reserved (GiB)": 234.63,
1608
+ "memory/max_active (GiB)": 186.82,
1609
+ "memory/max_allocated (GiB)": 186.82,
1610
+ "step": 160
1611
+ },
1612
+ {
1613
+ "epoch": 0.10959836623553437,
1614
+ "grad_norm": 0.9890943169593811,
1615
+ "learning_rate": 9.732198865788047e-06,
1616
+ "loss": 1.7266,
1617
+ "memory/device_reserved (GiB)": 234.63,
1618
+ "memory/max_active (GiB)": 186.82,
1619
+ "memory/max_allocated (GiB)": 186.82,
1620
+ "step": 161
1621
+ },
1622
+ {
1623
+ "epoch": 0.1102791014295439,
1624
+ "grad_norm": 0.9935751557350159,
1625
+ "learning_rate": 9.72871886401833e-06,
1626
+ "loss": 1.6527,
1627
+ "memory/device_reserved (GiB)": 234.63,
1628
+ "memory/max_active (GiB)": 186.82,
1629
+ "memory/max_allocated (GiB)": 186.82,
1630
+ "step": 162
1631
+ },
1632
+ {
1633
+ "epoch": 0.11095983662355344,
1634
+ "grad_norm": 0.7096329927444458,
1635
+ "learning_rate": 9.725217027493383e-06,
1636
+ "loss": 1.667,
1637
+ "memory/device_reserved (GiB)": 234.63,
1638
+ "memory/max_active (GiB)": 186.82,
1639
+ "memory/max_allocated (GiB)": 186.82,
1640
+ "step": 163
1641
+ },
1642
+ {
1643
+ "epoch": 0.11164057181756297,
1644
+ "grad_norm": 0.8332772850990295,
1645
+ "learning_rate": 9.721693372382863e-06,
1646
+ "loss": 1.7337,
1647
+ "memory/device_reserved (GiB)": 234.63,
1648
+ "memory/max_active (GiB)": 186.82,
1649
+ "memory/max_allocated (GiB)": 186.82,
1650
+ "step": 164
1651
+ },
1652
+ {
1653
+ "epoch": 0.1123213070115725,
1654
+ "grad_norm": 0.7919803857803345,
1655
+ "learning_rate": 9.718147914957166e-06,
1656
+ "loss": 1.576,
1657
+ "memory/device_reserved (GiB)": 234.63,
1658
+ "memory/max_active (GiB)": 186.82,
1659
+ "memory/max_allocated (GiB)": 186.82,
1660
+ "step": 165
1661
+ },
1662
+ {
1663
+ "epoch": 0.11300204220558203,
1664
+ "grad_norm": 0.8618379235267639,
1665
+ "learning_rate": 9.714580671587366e-06,
1666
+ "loss": 1.6249,
1667
+ "memory/device_reserved (GiB)": 234.63,
1668
+ "memory/max_active (GiB)": 186.82,
1669
+ "memory/max_allocated (GiB)": 186.82,
1670
+ "step": 166
1671
+ },
1672
+ {
1673
+ "epoch": 0.11368277739959155,
1674
+ "grad_norm": 0.7667165994644165,
1675
+ "learning_rate": 9.71099165874513e-06,
1676
+ "loss": 1.6761,
1677
+ "memory/device_reserved (GiB)": 234.63,
1678
+ "memory/max_active (GiB)": 186.82,
1679
+ "memory/max_allocated (GiB)": 186.82,
1680
+ "step": 167
1681
+ },
1682
+ {
1683
+ "epoch": 0.11436351259360109,
1684
+ "grad_norm": 0.6841418147087097,
1685
+ "learning_rate": 9.707380893002647e-06,
1686
+ "loss": 1.6868,
1687
+ "memory/device_reserved (GiB)": 234.63,
1688
+ "memory/max_active (GiB)": 186.82,
1689
+ "memory/max_allocated (GiB)": 186.82,
1690
+ "step": 168
1691
+ },
1692
+ {
1693
+ "epoch": 0.11504424778761062,
1694
+ "grad_norm": 0.6731845140457153,
1695
+ "learning_rate": 9.703748391032548e-06,
1696
+ "loss": 1.7487,
1697
+ "memory/device_reserved (GiB)": 234.63,
1698
+ "memory/max_active (GiB)": 186.82,
1699
+ "memory/max_allocated (GiB)": 186.82,
1700
+ "step": 169
1701
+ },
1702
+ {
1703
+ "epoch": 0.11572498298162015,
1704
+ "grad_norm": 0.7406771779060364,
1705
+ "learning_rate": 9.700094169607828e-06,
1706
+ "loss": 1.7071,
1707
+ "memory/device_reserved (GiB)": 234.63,
1708
+ "memory/max_active (GiB)": 186.82,
1709
+ "memory/max_allocated (GiB)": 186.82,
1710
+ "step": 170
1711
+ },
1712
+ {
1713
+ "epoch": 0.11640571817562968,
1714
+ "grad_norm": 0.7292412519454956,
1715
+ "learning_rate": 9.696418245601779e-06,
1716
+ "loss": 1.706,
1717
+ "memory/device_reserved (GiB)": 234.63,
1718
+ "memory/max_active (GiB)": 186.82,
1719
+ "memory/max_allocated (GiB)": 186.82,
1720
+ "step": 171
1721
+ },
1722
+ {
1723
+ "epoch": 0.11708645336963922,
1724
+ "grad_norm": 0.8011760711669922,
1725
+ "learning_rate": 9.692720635987893e-06,
1726
+ "loss": 1.7142,
1727
+ "memory/device_reserved (GiB)": 234.63,
1728
+ "memory/max_active (GiB)": 186.82,
1729
+ "memory/max_allocated (GiB)": 186.82,
1730
+ "step": 172
1731
+ },
1732
+ {
1733
+ "epoch": 0.11776718856364875,
1734
+ "grad_norm": 0.9184378385543823,
1735
+ "learning_rate": 9.689001357839807e-06,
1736
+ "loss": 1.7051,
1737
+ "memory/device_reserved (GiB)": 234.63,
1738
+ "memory/max_active (GiB)": 186.82,
1739
+ "memory/max_allocated (GiB)": 186.82,
1740
+ "step": 173
1741
+ },
1742
+ {
1743
+ "epoch": 0.11844792375765827,
1744
+ "grad_norm": 0.6435485482215881,
1745
+ "learning_rate": 9.685260428331203e-06,
1746
+ "loss": 1.736,
1747
+ "memory/device_reserved (GiB)": 234.63,
1748
+ "memory/max_active (GiB)": 186.82,
1749
+ "memory/max_allocated (GiB)": 186.82,
1750
+ "step": 174
1751
+ },
1752
+ {
1753
+ "epoch": 0.1191286589516678,
1754
+ "grad_norm": 0.8926677107810974,
1755
+ "learning_rate": 9.68149786473574e-06,
1756
+ "loss": 1.6661,
1757
+ "memory/device_reserved (GiB)": 234.63,
1758
+ "memory/max_active (GiB)": 186.82,
1759
+ "memory/max_allocated (GiB)": 186.82,
1760
+ "step": 175
1761
+ },
1762
+ {
1763
+ "epoch": 0.11980939414567733,
1764
+ "grad_norm": 0.6705238819122314,
1765
+ "learning_rate": 9.677713684426973e-06,
1766
+ "loss": 1.6917,
1767
+ "memory/device_reserved (GiB)": 234.63,
1768
+ "memory/max_active (GiB)": 186.82,
1769
+ "memory/max_allocated (GiB)": 186.82,
1770
+ "step": 176
1771
+ },
1772
+ {
1773
+ "epoch": 0.12049012933968686,
1774
+ "grad_norm": 0.6798558831214905,
1775
+ "learning_rate": 9.673907904878272e-06,
1776
+ "loss": 1.6402,
1777
+ "memory/device_reserved (GiB)": 234.63,
1778
+ "memory/max_active (GiB)": 186.82,
1779
+ "memory/max_allocated (GiB)": 186.82,
1780
+ "step": 177
1781
+ },
1782
+ {
1783
+ "epoch": 0.1211708645336964,
1784
+ "grad_norm": 0.6277421712875366,
1785
+ "learning_rate": 9.670080543662742e-06,
1786
+ "loss": 1.6738,
1787
+ "memory/device_reserved (GiB)": 234.63,
1788
+ "memory/max_active (GiB)": 186.82,
1789
+ "memory/max_allocated (GiB)": 186.82,
1790
+ "step": 178
1791
+ },
1792
+ {
1793
+ "epoch": 0.12185159972770593,
1794
+ "grad_norm": 0.6391667723655701,
1795
+ "learning_rate": 9.666231618453135e-06,
1796
+ "loss": 1.6823,
1797
+ "memory/device_reserved (GiB)": 234.63,
1798
+ "memory/max_active (GiB)": 186.82,
1799
+ "memory/max_allocated (GiB)": 186.82,
1800
+ "step": 179
1801
+ },
1802
+ {
1803
+ "epoch": 0.12253233492171545,
1804
+ "grad_norm": 0.6664396524429321,
1805
+ "learning_rate": 9.66236114702178e-06,
1806
+ "loss": 1.7058,
1807
+ "memory/device_reserved (GiB)": 234.63,
1808
+ "memory/max_active (GiB)": 186.82,
1809
+ "memory/max_allocated (GiB)": 186.82,
1810
+ "step": 180
1811
+ },
1812
+ {
1813
+ "epoch": 0.12321307011572498,
1814
+ "grad_norm": 1.5816713571548462,
1815
+ "learning_rate": 9.658469147240494e-06,
1816
+ "loss": 1.7435,
1817
+ "memory/device_reserved (GiB)": 234.63,
1818
+ "memory/max_active (GiB)": 186.82,
1819
+ "memory/max_allocated (GiB)": 186.82,
1820
+ "step": 181
1821
+ },
1822
+ {
1823
+ "epoch": 0.12389380530973451,
1824
+ "grad_norm": 8.72884750366211,
1825
+ "learning_rate": 9.654555637080503e-06,
1826
+ "loss": 1.6991,
1827
+ "memory/device_reserved (GiB)": 234.63,
1828
+ "memory/max_active (GiB)": 186.82,
1829
+ "memory/max_allocated (GiB)": 186.82,
1830
+ "step": 182
1831
+ },
1832
+ {
1833
+ "epoch": 0.12457454050374404,
1834
+ "grad_norm": 1.1152446269989014,
1835
+ "learning_rate": 9.65062063461235e-06,
1836
+ "loss": 1.7147,
1837
+ "memory/device_reserved (GiB)": 234.63,
1838
+ "memory/max_active (GiB)": 186.82,
1839
+ "memory/max_allocated (GiB)": 186.82,
1840
+ "step": 183
1841
+ },
1842
+ {
1843
+ "epoch": 0.12525527569775358,
1844
+ "grad_norm": 0.953542172908783,
1845
+ "learning_rate": 9.646664158005823e-06,
1846
+ "loss": 1.7064,
1847
+ "memory/device_reserved (GiB)": 234.63,
1848
+ "memory/max_active (GiB)": 186.82,
1849
+ "memory/max_allocated (GiB)": 186.82,
1850
+ "step": 184
1851
+ },
1852
+ {
1853
+ "epoch": 0.1259360108917631,
1854
+ "grad_norm": 0.8553478717803955,
1855
+ "learning_rate": 9.642686225529864e-06,
1856
+ "loss": 1.683,
1857
+ "memory/device_reserved (GiB)": 234.63,
1858
+ "memory/max_active (GiB)": 186.82,
1859
+ "memory/max_allocated (GiB)": 186.82,
1860
+ "step": 185
1861
+ },
1862
+ {
1863
+ "epoch": 0.12661674608577264,
1864
+ "grad_norm": 1.008264422416687,
1865
+ "learning_rate": 9.638686855552494e-06,
1866
+ "loss": 1.6093,
1867
+ "memory/device_reserved (GiB)": 234.63,
1868
+ "memory/max_active (GiB)": 186.82,
1869
+ "memory/max_allocated (GiB)": 186.82,
1870
+ "step": 186
1871
+ },
1872
+ {
1873
+ "epoch": 0.12729748127978216,
1874
+ "grad_norm": 0.8719388246536255,
1875
+ "learning_rate": 9.634666066540713e-06,
1876
+ "loss": 1.7384,
1877
+ "memory/device_reserved (GiB)": 234.63,
1878
+ "memory/max_active (GiB)": 186.82,
1879
+ "memory/max_allocated (GiB)": 186.82,
1880
+ "step": 187
1881
+ },
1882
+ {
1883
+ "epoch": 0.1279782164737917,
1884
+ "grad_norm": 1.1259270906448364,
1885
+ "learning_rate": 9.630623877060423e-06,
1886
+ "loss": 1.7397,
1887
+ "memory/device_reserved (GiB)": 234.63,
1888
+ "memory/max_active (GiB)": 186.82,
1889
+ "memory/max_allocated (GiB)": 186.82,
1890
+ "step": 188
1891
+ },
1892
+ {
1893
+ "epoch": 0.12865895166780122,
1894
+ "grad_norm": 1.1336485147476196,
1895
+ "learning_rate": 9.626560305776349e-06,
1896
+ "loss": 1.6912,
1897
+ "memory/device_reserved (GiB)": 234.63,
1898
+ "memory/max_active (GiB)": 186.82,
1899
+ "memory/max_allocated (GiB)": 186.82,
1900
+ "step": 189
1901
+ },
1902
+ {
1903
+ "epoch": 0.12933968686181074,
1904
+ "grad_norm": 1.1066447496414185,
1905
+ "learning_rate": 9.62247537145194e-06,
1906
+ "loss": 1.667,
1907
+ "memory/device_reserved (GiB)": 234.63,
1908
+ "memory/max_active (GiB)": 186.82,
1909
+ "memory/max_allocated (GiB)": 186.82,
1910
+ "step": 190
1911
+ },
1912
+ {
1913
+ "epoch": 0.1300204220558203,
1914
+ "grad_norm": 0.8986105918884277,
1915
+ "learning_rate": 9.618369092949289e-06,
1916
+ "loss": 1.7657,
1917
+ "memory/device_reserved (GiB)": 234.63,
1918
+ "memory/max_active (GiB)": 186.82,
1919
+ "memory/max_allocated (GiB)": 186.82,
1920
+ "step": 191
1921
+ },
1922
+ {
1923
+ "epoch": 0.1307011572498298,
1924
+ "grad_norm": 0.7317138314247131,
1925
+ "learning_rate": 9.61424148922905e-06,
1926
+ "loss": 1.6715,
1927
+ "memory/device_reserved (GiB)": 234.63,
1928
+ "memory/max_active (GiB)": 186.82,
1929
+ "memory/max_allocated (GiB)": 186.82,
1930
+ "step": 192
1931
+ },
1932
+ {
1933
+ "epoch": 0.13138189244383935,
1934
+ "grad_norm": 0.6420246362686157,
1935
+ "learning_rate": 9.610092579350339e-06,
1936
+ "loss": 1.6346,
1937
+ "memory/device_reserved (GiB)": 234.63,
1938
+ "memory/max_active (GiB)": 186.82,
1939
+ "memory/max_allocated (GiB)": 186.82,
1940
+ "step": 193
1941
+ },
1942
+ {
1943
+ "epoch": 0.13206262763784887,
1944
+ "grad_norm": 0.7444735765457153,
1945
+ "learning_rate": 9.605922382470659e-06,
1946
+ "loss": 1.6846,
1947
+ "memory/device_reserved (GiB)": 234.63,
1948
+ "memory/max_active (GiB)": 186.82,
1949
+ "memory/max_allocated (GiB)": 186.82,
1950
+ "step": 194
1951
+ },
1952
+ {
1953
+ "epoch": 0.13274336283185842,
1954
+ "grad_norm": 0.9247352480888367,
1955
+ "learning_rate": 9.601730917845798e-06,
1956
+ "loss": 1.6513,
1957
+ "memory/device_reserved (GiB)": 234.63,
1958
+ "memory/max_active (GiB)": 186.82,
1959
+ "memory/max_allocated (GiB)": 186.82,
1960
+ "step": 195
1961
+ },
1962
+ {
1963
+ "epoch": 0.13342409802586794,
1964
+ "grad_norm": 0.7954132556915283,
1965
+ "learning_rate": 9.597518204829755e-06,
1966
+ "loss": 1.7392,
1967
+ "memory/device_reserved (GiB)": 234.63,
1968
+ "memory/max_active (GiB)": 186.82,
1969
+ "memory/max_allocated (GiB)": 186.82,
1970
+ "step": 196
1971
+ },
1972
+ {
1973
+ "epoch": 0.13410483321987746,
1974
+ "grad_norm": 0.7020078301429749,
1975
+ "learning_rate": 9.59328426287464e-06,
1976
+ "loss": 1.6942,
1977
+ "memory/device_reserved (GiB)": 234.63,
1978
+ "memory/max_active (GiB)": 186.82,
1979
+ "memory/max_allocated (GiB)": 186.82,
1980
+ "step": 197
1981
+ },
1982
+ {
1983
+ "epoch": 0.134785568413887,
1984
+ "grad_norm": 0.7420036792755127,
1985
+ "learning_rate": 9.589029111530585e-06,
1986
+ "loss": 1.7682,
1987
+ "memory/device_reserved (GiB)": 234.63,
1988
+ "memory/max_active (GiB)": 186.82,
1989
+ "memory/max_allocated (GiB)": 186.82,
1990
+ "step": 198
1991
+ },
1992
+ {
1993
+ "epoch": 0.13546630360789652,
1994
+ "grad_norm": 0.7332531213760376,
1995
+ "learning_rate": 9.584752770445658e-06,
1996
+ "loss": 1.7433,
1997
+ "memory/device_reserved (GiB)": 234.63,
1998
+ "memory/max_active (GiB)": 186.82,
1999
+ "memory/max_allocated (GiB)": 186.82,
2000
+ "step": 199
2001
+ },
2002
+ {
2003
+ "epoch": 0.13614703880190607,
2004
+ "grad_norm": 0.6352435946464539,
2005
+ "learning_rate": 9.58045525936577e-06,
2006
+ "loss": 1.706,
2007
+ "memory/device_reserved (GiB)": 234.63,
2008
+ "memory/max_active (GiB)": 186.82,
2009
+ "memory/max_allocated (GiB)": 186.82,
2010
+ "step": 200
2011
+ }
2012
+ ],
2013
+ "logging_steps": 1,
2014
+ "max_steps": 1469,
2015
+ "num_input_tokens_seen": 0,
2016
+ "num_train_epochs": 1,
2017
+ "save_steps": 50,
2018
+ "stateful_callbacks": {
2019
+ "TrainerControl": {
2020
+ "args": {
2021
+ "should_epoch_stop": false,
2022
+ "should_evaluate": false,
2023
+ "should_log": false,
2024
+ "should_save": true,
2025
+ "should_training_stop": false
2026
+ },
2027
+ "attributes": {}
2028
+ }
2029
+ },
2030
+ "total_flos": 2.5488598918372524e+19,
2031
+ "train_batch_size": 12,
2032
+ "trial_name": null,
2033
+ "trial_params": null
2034
+ }
vocab.json ADDED
The diff for this file is too large to render. See raw diff