Adzka/reward-model-distilbert-indo

README.md

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+---
+license: mit
+base_model: w11wo/indonesian-roberta-base-sentiment-classifier
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: train-reward-training
+  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. -->
+
+# train-reward-training
+
+This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4306
+- Accuracy: 0.8197
+
+## 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: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 12
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7102        | 0.57  | 50   | 0.6741          | 0.7623   |
+| 0.6583        | 1.15  | 100  | 0.6248          | 0.7705   |
+| 0.5738        | 1.72  | 150  | 0.5009          | 0.8115   |
+| 0.438         | 2.3   | 200  | 0.3925          | 0.8443   |
+| 0.3201        | 2.87  | 250  | 0.3594          | 0.8361   |
+| 0.2535        | 3.45  | 300  | 0.3908          | 0.8361   |
+| 0.1875        | 4.02  | 350  | 0.3669          | 0.8443   |
+| 0.1249        | 4.6   | 400  | 0.3908          | 0.8279   |
+| 0.1205        | 5.17  | 450  | 0.4065          | 0.8525   |
+| 0.1083        | 5.75  | 500  | 0.4077          | 0.8443   |
+| 0.0586        | 6.32  | 550  | 0.3901          | 0.8361   |
+| 0.0998        | 6.9   | 600  | 0.4196          | 0.8525   |
+| 0.0634        | 7.47  | 650  | 0.4174          | 0.8525   |
+| 0.0491        | 8.05  | 700  | 0.4311          | 0.8443   |
+| 0.0354        | 8.62  | 750  | 0.4140          | 0.8279   |
+| 0.0375        | 9.2   | 800  | 0.4205          | 0.8115   |
+| 0.0343        | 9.77  | 850  | 0.4212          | 0.8197   |
+| 0.0372        | 10.34 | 900  | 0.4132          | 0.8197   |
+| 0.0238        | 10.92 | 950  | 0.4306          | 0.8197   |
+| 0.0299        | 11.49 | 1000 | 0.4270          | 0.8197   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.5
+- Tokenizers 0.15.2

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