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-r8a1d0.15-0
+  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-r8a1d0.15-0
+
+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: 0.3217
+- Accuracy: 0.8622
+- Precision: 0.8326
+- Recall: 0.8375
+- F1: 0.8349
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5593        | 1.0   | 122  | 0.5026          | 0.7268   | 0.6658    | 0.6542 | 0.6589 |
+| 0.4995        | 2.0   | 244  | 0.4797          | 0.7544   | 0.7149    | 0.7412 | 0.7226 |
+| 0.4612        | 3.0   | 366  | 0.4282          | 0.7644   | 0.7199    | 0.7358 | 0.7262 |
+| 0.4019        | 4.0   | 488  | 0.3934          | 0.8296   | 0.7949    | 0.7919 | 0.7934 |
+| 0.3665        | 5.0   | 610  | 0.4234          | 0.7970   | 0.7618    | 0.7964 | 0.7720 |
+| 0.334         | 6.0   | 732  | 0.3723          | 0.8195   | 0.7817    | 0.7973 | 0.7884 |
+| 0.3263        | 7.0   | 854  | 0.3704          | 0.8346   | 0.7990    | 0.8230 | 0.8086 |
+| 0.3076        | 8.0   | 976  | 0.3521          | 0.8471   | 0.8153    | 0.8168 | 0.8160 |
+| 0.298         | 9.0   | 1098 | 0.3522          | 0.8471   | 0.8138    | 0.8243 | 0.8187 |
+| 0.2923        | 10.0  | 1220 | 0.3375          | 0.8571   | 0.8289    | 0.8239 | 0.8264 |
+| 0.2689        | 11.0  | 1342 | 0.3392          | 0.8622   | 0.8319    | 0.8400 | 0.8357 |
+| 0.2686        | 12.0  | 1464 | 0.3484          | 0.8622   | 0.8309    | 0.8450 | 0.8373 |
+| 0.2726        | 13.0  | 1586 | 0.3258          | 0.8596   | 0.8316    | 0.8282 | 0.8298 |
+| 0.2713        | 14.0  | 1708 | 0.3246          | 0.8622   | 0.8333    | 0.8350 | 0.8341 |
+| 0.2577        | 15.0  | 1830 | 0.3307          | 0.8596   | 0.8293    | 0.8357 | 0.8324 |
+| 0.2519        | 16.0  | 1952 | 0.3305          | 0.8622   | 0.8314    | 0.8425 | 0.8365 |
+| 0.2488        | 17.0  | 2074 | 0.3234          | 0.8546   | 0.8246    | 0.8246 | 0.8246 |
+| 0.2546        | 18.0  | 2196 | 0.3247          | 0.8647   | 0.8346    | 0.8442 | 0.8391 |
+| 0.2463        | 19.0  | 2318 | 0.3204          | 0.8596   | 0.8307    | 0.8307 | 0.8307 |
+| 0.2458        | 20.0  | 2440 | 0.3217          | 0.8622   | 0.8326    | 0.8375 | 0.8349 |
+
+
+### 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/May18_01-27-31_indolem-petl-vm/events.out.tfevents.1715995656.indolem-petl-vm.1514751.0

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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": 0.15,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 8,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "d7a928f95cb5f33d",
+  "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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+    "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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