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-r16a1d0.1-0
+  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-r16a1d0.1-0
+
+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: 0.2912
+- Accuracy: 0.8647
+- Precision: 0.8346
+- Recall: 0.8442
+- F1: 0.8391
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.559         | 1.0   | 122  | 0.5023          | 0.7268   | 0.6671    | 0.6592 | 0.6627 |
+| 0.4818        | 2.0   | 244  | 0.4518          | 0.7569   | 0.7248    | 0.7605 | 0.7318 |
+| 0.4129        | 3.0   | 366  | 0.3967          | 0.8246   | 0.7876    | 0.7959 | 0.7914 |
+| 0.3519        | 4.0   | 488  | 0.3626          | 0.8496   | 0.8193    | 0.8161 | 0.8177 |
+| 0.3191        | 5.0   | 610  | 0.3720          | 0.8471   | 0.8130    | 0.8393 | 0.8235 |
+| 0.2977        | 6.0   | 732  | 0.3482          | 0.8546   | 0.8216    | 0.8422 | 0.8303 |
+| 0.2861        | 7.0   | 854  | 0.3343          | 0.8672   | 0.8363    | 0.8535 | 0.8439 |
+| 0.2662        | 8.0   | 976  | 0.3213          | 0.8622   | 0.8314    | 0.8425 | 0.8365 |
+| 0.2618        | 9.0   | 1098 | 0.3246          | 0.8697   | 0.8399    | 0.8528 | 0.8458 |
+| 0.2556        | 10.0  | 1220 | 0.3065          | 0.8596   | 0.8307    | 0.8307 | 0.8307 |
+| 0.2353        | 11.0  | 1342 | 0.3148          | 0.8722   | 0.8416    | 0.8621 | 0.8505 |
+| 0.24          | 12.0  | 1464 | 0.3098          | 0.8747   | 0.8451    | 0.8613 | 0.8524 |
+| 0.2346        | 13.0  | 1586 | 0.2989          | 0.8772   | 0.8524    | 0.8506 | 0.8515 |
+| 0.2367        | 14.0  | 1708 | 0.3001          | 0.8697   | 0.8399    | 0.8528 | 0.8458 |
+| 0.2248        | 15.0  | 1830 | 0.3040          | 0.8722   | 0.8420    | 0.8596 | 0.8498 |
+| 0.2174        | 16.0  | 1952 | 0.3016          | 0.8697   | 0.8386    | 0.8603 | 0.8479 |
+| 0.2112        | 17.0  | 2074 | 0.2887          | 0.8647   | 0.8346    | 0.8442 | 0.8391 |
+| 0.2162        | 18.0  | 2196 | 0.2980          | 0.8722   | 0.8416    | 0.8621 | 0.8505 |
+| 0.2124        | 19.0  | 2318 | 0.2892          | 0.8697   | 0.8411    | 0.8478 | 0.8443 |
+| 0.2118        | 20.0  | 2440 | 0.2912          | 0.8647   | 0.8346    | 0.8442 | 0.8391 |
+
+
+### 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/May26_16-34-51_indolem-petl-vm/events.out.tfevents.1716741297.indolem-petl-vm.2979451.0

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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": 0.1,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 16,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "721abbf94cae4bba",
+  "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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+      "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"
+}

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