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-r8a0d0.1-0
+  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-r8a0d0.1-0
+
+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: 0.3309
+- Accuracy: 0.8672
+- Precision: 0.8378
+- Recall: 0.8460
+- F1: 0.8417
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5622        | 1.0   | 122  | 0.5076          | 0.7193   | 0.6565    | 0.6464 | 0.6505 |
+| 0.5003        | 2.0   | 244  | 0.4839          | 0.7469   | 0.7107    | 0.7409 | 0.7178 |
+| 0.4614        | 3.0   | 366  | 0.4256          | 0.7719   | 0.7281    | 0.7436 | 0.7344 |
+| 0.4022        | 4.0   | 488  | 0.3880          | 0.8170   | 0.7798    | 0.7756 | 0.7776 |
+| 0.3678        | 5.0   | 610  | 0.4131          | 0.8020   | 0.7657    | 0.7974 | 0.7760 |
+| 0.3376        | 6.0   | 732  | 0.3645          | 0.8321   | 0.7965    | 0.8037 | 0.7999 |
+| 0.3268        | 7.0   | 854  | 0.3640          | 0.8346   | 0.7988    | 0.8180 | 0.8069 |
+| 0.3044        | 8.0   | 976  | 0.3551          | 0.8346   | 0.7996    | 0.8055 | 0.8024 |
+| 0.2984        | 9.0   | 1098 | 0.3509          | 0.8496   | 0.8169    | 0.8261 | 0.8212 |
+| 0.2922        | 10.0  | 1220 | 0.3413          | 0.8521   | 0.8213    | 0.8229 | 0.8221 |
+| 0.2666        | 11.0  | 1342 | 0.3494          | 0.8521   | 0.8193    | 0.8329 | 0.8254 |
+| 0.2641        | 12.0  | 1464 | 0.3520          | 0.8546   | 0.8220    | 0.8372 | 0.8288 |
+| 0.2694        | 13.0  | 1586 | 0.3358          | 0.8496   | 0.8202    | 0.8136 | 0.8167 |
+| 0.2678        | 14.0  | 1708 | 0.3355          | 0.8647   | 0.8352    | 0.8417 | 0.8383 |
+| 0.255         | 15.0  | 1830 | 0.3406          | 0.8647   | 0.8346    | 0.8442 | 0.8391 |
+| 0.2482        | 16.0  | 1952 | 0.3370          | 0.8622   | 0.8309    | 0.8450 | 0.8373 |
+| 0.2444        | 17.0  | 2074 | 0.3272          | 0.8697   | 0.8411    | 0.8478 | 0.8443 |
+| 0.2521        | 18.0  | 2196 | 0.3319          | 0.8622   | 0.8314    | 0.8425 | 0.8365 |
+| 0.2456        | 19.0  | 2318 | 0.3293          | 0.8697   | 0.8411    | 0.8478 | 0.8443 |
+| 0.2458        | 20.0  | 2440 | 0.3309          | 0.8672   | 0.8378    | 0.8460 | 0.8417 |
+
+
+### 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/May17_23-13-38_indolem-petl-vm/events.out.tfevents.1715987622.indolem-petl-vm.1474600.0

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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": 8,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "9a6df5ed9051a32d",
+  "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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