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-r4a1d0.05-1
+  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-r4a1d0.05-1
+
+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: 0.3356
+- Accuracy: 0.8622
+- Precision: 0.8399
+- Recall: 0.8200
+- F1: 0.8289
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5657        | 1.0   | 122  | 0.5182          | 0.7243   | 0.6604    | 0.6424 | 0.6488 |
+| 0.5109        | 2.0   | 244  | 0.5051          | 0.7243   | 0.6748    | 0.6874 | 0.6796 |
+| 0.48          | 3.0   | 366  | 0.4643          | 0.7569   | 0.7047    | 0.6880 | 0.6948 |
+| 0.434         | 4.0   | 488  | 0.4281          | 0.7920   | 0.7497    | 0.7378 | 0.7431 |
+| 0.4106        | 5.0   | 610  | 0.4194          | 0.7920   | 0.7528    | 0.7778 | 0.7618 |
+| 0.3812        | 6.0   | 732  | 0.3936          | 0.8296   | 0.8008    | 0.7744 | 0.7854 |
+| 0.3689        | 7.0   | 854  | 0.3700          | 0.8521   | 0.8220    | 0.8204 | 0.8212 |
+| 0.3489        | 8.0   | 976  | 0.3656          | 0.8346   | 0.8088    | 0.7780 | 0.7905 |
+| 0.3502        | 9.0   | 1098 | 0.3640          | 0.8371   | 0.8101    | 0.7847 | 0.7955 |
+| 0.3349        | 10.0  | 1220 | 0.3608          | 0.8346   | 0.8074    | 0.7805 | 0.7917 |
+| 0.3189        | 11.0  | 1342 | 0.3574          | 0.8396   | 0.8128    | 0.7890 | 0.7992 |
+| 0.3121        | 12.0  | 1464 | 0.3547          | 0.8471   | 0.8175    | 0.8093 | 0.8132 |
+| 0.3181        | 13.0  | 1586 | 0.3478          | 0.8521   | 0.8332    | 0.7979 | 0.8122 |
+| 0.3092        | 14.0  | 1708 | 0.3435          | 0.8596   | 0.8374    | 0.8157 | 0.8253 |
+| 0.3018        | 15.0  | 1830 | 0.3466          | 0.8546   | 0.8296    | 0.8121 | 0.8200 |
+| 0.2955        | 16.0  | 1952 | 0.3365          | 0.8596   | 0.8347    | 0.8207 | 0.8272 |
+| 0.2917        | 17.0  | 2074 | 0.3353          | 0.8596   | 0.8374    | 0.8157 | 0.8253 |
+| 0.2956        | 18.0  | 2196 | 0.3379          | 0.8596   | 0.8360    | 0.8182 | 0.8262 |
+| 0.2899        | 19.0  | 2318 | 0.3353          | 0.8647   | 0.8455    | 0.8192 | 0.8306 |
+| 0.2885        | 20.0  | 2440 | 0.3356          | 0.8622   | 0.8399    | 0.8200 | 0.8289 |
+
+
+### 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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+{
+  "config": {
+    "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_00-58-56_indolem-petl-vm/events.out.tfevents.1716080341.indolem-petl-vm.2026936.0

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sentiment-lora/adapter_config.json

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+{
+  "config": {
+    "alpha": 1,
+    "architecture": "lora",
+    "attn_matrices": [
+      "q",
+      "v"
+    ],
+    "composition_mode": "add",
+    "dropout": 0.05,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 4,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "23d8ce29982cde2d",
+  "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": {
+      "0": 0,
+      "1": 1
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+    "layers": 2,
+    "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"
+}

sentiment/pytorch_model_head.bin

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