Model save

README.md

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+---
+license: mit
+base_model: indolem/indobert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: sentiment-lora-r4a2d0.15-1
+  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. -->
+
+# sentiment-lora-r4a2d0.15-1
+
+This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3312
+- Accuracy: 0.8622
+- Precision: 0.8414
+- Recall: 0.8175
+- F1: 0.8279
+
+## 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-05
+- train_batch_size: 30
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.566         | 1.0   | 122  | 0.5206          | 0.7143   | 0.6484    | 0.6353 | 0.6403 |
+| 0.5117        | 2.0   | 244  | 0.5062          | 0.7343   | 0.6880    | 0.7045 | 0.6939 |
+| 0.4804        | 3.0   | 366  | 0.4667          | 0.7669   | 0.7182    | 0.7126 | 0.7152 |
+| 0.4345        | 4.0   | 488  | 0.4350          | 0.7920   | 0.7494    | 0.7403 | 0.7445 |
+| 0.4081        | 5.0   | 610  | 0.4337          | 0.7945   | 0.7565    | 0.7846 | 0.7661 |
+| 0.3793        | 6.0   | 732  | 0.3923          | 0.8195   | 0.7857    | 0.7673 | 0.7753 |
+| 0.3665        | 7.0   | 854  | 0.3765          | 0.8296   | 0.7949    | 0.7919 | 0.7934 |
+| 0.3471        | 8.0   | 976  | 0.3681          | 0.8371   | 0.8089    | 0.7872 | 0.7966 |
+| 0.3498        | 9.0   | 1098 | 0.3677          | 0.8321   | 0.8024    | 0.7812 | 0.7904 |
+| 0.3282        | 10.0  | 1220 | 0.3634          | 0.8346   | 0.8074    | 0.7805 | 0.7917 |
+| 0.3149        | 11.0  | 1342 | 0.3537          | 0.8446   | 0.8180    | 0.7976 | 0.8065 |
+| 0.3092        | 12.0  | 1464 | 0.3529          | 0.8496   | 0.8202    | 0.8136 | 0.8167 |
+| 0.3135        | 13.0  | 1586 | 0.3471          | 0.8521   | 0.8332    | 0.7979 | 0.8122 |
+| 0.3103        | 14.0  | 1708 | 0.3427          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
+| 0.2974        | 15.0  | 1830 | 0.3372          | 0.8622   | 0.8385    | 0.8225 | 0.8298 |
+| 0.2905        | 16.0  | 1952 | 0.3345          | 0.8697   | 0.8488    | 0.8303 | 0.8386 |
+| 0.2895        | 17.0  | 2074 | 0.3339          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
+| 0.2922        | 18.0  | 2196 | 0.3319          | 0.8697   | 0.8488    | 0.8303 | 0.8386 |
+| 0.2843        | 19.0  | 2318 | 0.3319          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
+| 0.287         | 20.0  | 2440 | 0.3312          | 0.8622   | 0.8414    | 0.8175 | 0.8279 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.15.2

default/head_config.json

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+    "activation_function": "gelu",
+    "bias": true,
+    "embedding_size": 768,
+    "head_type": "masked_lm",
+    "label2id": null,
+    "layer_norm": true,
+    "layers": 2,
+    "shift_labels": false,
+    "vocab_size": 31923
+  },
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "default",
+  "version": "0.2.0"
+}

default/pytorch_model_head.bin

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runs/May19_03-46-18_indolem-petl-vm/events.out.tfevents.1716090382.indolem-petl-vm.2093084.0

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sentiment-lora/adapter_config.json

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+{
+  "config": {
+    "alpha": 2,
+    "architecture": "lora",
+    "attn_matrices": [
+      "q",
+      "v"
+    ],
+    "composition_mode": "add",
+    "dropout": 0.15,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 4,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "d658784d9d7679ac",
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "sentiment-lora",
+  "version": "0.2.0"
+}

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sentiment/head_config.json

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+  "config": {
+    "activation_function": "tanh",
+    "bias": true,
+    "dropout_prob": null,
+    "head_type": "classification",
+    "label2id": {
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+    "num_labels": 2,
+    "use_pooler": false
+  },
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "sentiment",
+  "version": "0.2.0"
+}

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