Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM2-1.7B
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: smollm_1_7B_tulu3
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# smollm_1_7B_tulu3
+
+This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7824
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- total_eval_batch_size: 64
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3348        | 0.0551 | 200  | 1.2704          |
+| 1.0411        | 0.1101 | 400  | 1.0435          |
+| 1.0483        | 0.1652 | 600  | 0.9694          |
+| 0.8801        | 0.2202 | 800  | 0.9227          |
+| 0.8996        | 0.2753 | 1000 | 0.8888          |
+| 0.8682        | 0.3303 | 1200 | 0.8648          |
+| 0.8757        | 0.3854 | 1400 | 0.8468          |
+| 0.8441        | 0.4404 | 1600 | 0.8311          |
+| 0.8197        | 0.4955 | 1800 | 0.8206          |
+| 0.7807        | 0.5505 | 2000 | 0.8090          |
+| 0.7757        | 0.6056 | 2200 | 0.8015          |
+| 0.7818        | 0.6607 | 2400 | 0.7957          |
+| 0.8235        | 0.7157 | 2600 | 0.7915          |
+| 0.7854        | 0.7708 | 2800 | 0.7883          |
+| 0.7958        | 0.8258 | 3000 | 0.7863          |
+| 0.8192        | 0.8809 | 3200 | 0.7829          |
+| 0.765         | 0.9359 | 3400 | 0.7824          |
+| 0.7939        | 0.9910 | 3600 | 0.7824          |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.0

all_results.json

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+{
+    "epoch": 0.99979354483518,
+    "total_flos": 1258708224212992.0,
+    "train_loss": 0.935843440076328,
+    "train_runtime": 26049.5256,
+    "train_samples": 929949,
+    "train_samples_per_second": 35.699,
+    "train_steps_per_second": 0.139
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 49152,
+  "transformers_version": "4.48.3"
+}

train_results.json

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+{
+    "epoch": 0.99979354483518,
+    "total_flos": 1258708224212992.0,
+    "train_loss": 0.935843440076328,
+    "train_runtime": 26049.5256,
+    "train_samples": 929949,
+    "train_samples_per_second": 35.699,
+    "train_steps_per_second": 0.139
+}