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-r4a0d0.1-1
+  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-r4a0d0.1-1
+
+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: 0.3239
+- Accuracy: 0.8622
+- Precision: 0.8373
+- Recall: 0.8250
+- F1: 0.8307
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5658        | 1.0   | 122  | 0.5195          | 0.7268   | 0.6646    | 0.6492 | 0.6550 |
+| 0.5125        | 2.0   | 244  | 0.5060          | 0.7293   | 0.6805    | 0.6935 | 0.6855 |
+| 0.4809        | 3.0   | 366  | 0.4686          | 0.7669   | 0.7184    | 0.7151 | 0.7167 |
+| 0.4353        | 4.0   | 488  | 0.4295          | 0.7920   | 0.7500    | 0.7353 | 0.7417 |
+| 0.4116        | 5.0   | 610  | 0.4171          | 0.8020   | 0.7628    | 0.7849 | 0.7714 |
+| 0.3809        | 6.0   | 732  | 0.3865          | 0.8446   | 0.8148    | 0.8051 | 0.8096 |
+| 0.3681        | 7.0   | 854  | 0.3697          | 0.8496   | 0.8193    | 0.8161 | 0.8177 |
+| 0.3469        | 8.0   | 976  | 0.3554          | 0.8471   | 0.8206    | 0.8018 | 0.8102 |
+| 0.3455        | 9.0   | 1098 | 0.3494          | 0.8496   | 0.8211    | 0.8111 | 0.8158 |
+| 0.3284        | 10.0  | 1220 | 0.3437          | 0.8496   | 0.8289    | 0.7961 | 0.8096 |
+| 0.3132        | 11.0  | 1342 | 0.3371          | 0.8596   | 0.8389    | 0.8132 | 0.8243 |
+| 0.3042        | 12.0  | 1464 | 0.3371          | 0.8546   | 0.8254    | 0.8221 | 0.8238 |
+| 0.3063        | 13.0  | 1586 | 0.3317          | 0.8596   | 0.8406    | 0.8107 | 0.8233 |
+| 0.3013        | 14.0  | 1708 | 0.3304          | 0.8622   | 0.8373    | 0.8250 | 0.8307 |
+| 0.2928        | 15.0  | 1830 | 0.3295          | 0.8596   | 0.8325    | 0.8257 | 0.8290 |
+| 0.2864        | 16.0  | 1952 | 0.3284          | 0.8622   | 0.8351    | 0.8300 | 0.8325 |
+| 0.2819        | 17.0  | 2074 | 0.3254          | 0.8596   | 0.8347    | 0.8207 | 0.8272 |
+| 0.2877        | 18.0  | 2196 | 0.3249          | 0.8596   | 0.8336    | 0.8232 | 0.8281 |
+| 0.2819        | 19.0  | 2318 | 0.3241          | 0.8647   | 0.8410    | 0.8267 | 0.8333 |
+| 0.2803        | 20.0  | 2440 | 0.3239          | 0.8622   | 0.8373    | 0.8250 | 0.8307 |
+
+
+### 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/May18_23-51-56_indolem-petl-vm/events.out.tfevents.1716076320.indolem-petl-vm.2003960.0

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sentiment-lora/adapter_config.json

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+{
+  "config": {
+    "alpha": 0,
+    "architecture": "lora",
+    "attn_matrices": [
+      "q",
+      "v"
+    ],
+    "composition_mode": "add",
+    "dropout": 0.1,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 4,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "e496874b2522628a",
+  "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"
+}

sentiment/pytorch_model_head.bin

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