End of training

README.md

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+---
+license: mit
+base_model: indobenchmark/indobert-base-p2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: reward_model
+  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. -->
+
+# reward_model
+
+This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3276
+- Accuracy: 0.8701
+- F1: 0.8832
+- Precision: 0.87
+- Recall: 0.8969
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 89   | 0.3276          | 0.8701   | 0.8832 | 0.87      | 0.8969 |
+| No log        | 2.0   | 178  | 0.3607          | 0.8588   | 0.8744 | 0.8529    | 0.8969 |
+| No log        | 3.0   | 267  | 0.4801          | 0.8870   | 0.9    | 0.8738    | 0.9278 |
+| No log        | 4.0   | 356  | 0.5740          | 0.8870   | 0.8990 | 0.8812    | 0.9175 |
+| No log        | 5.0   | 445  | 0.5676          | 0.9040   | 0.9119 | 0.9167    | 0.9072 |
+| 0.1393        | 6.0   | 534  | 0.6471          | 0.9040   | 0.9128 | 0.9082    | 0.9175 |
+| 0.1393        | 7.0   | 623  | 0.6998          | 0.8870   | 0.8990 | 0.8812    | 0.9175 |
+| 0.1393        | 8.0   | 712  | 0.7484          | 0.8870   | 0.8990 | 0.8812    | 0.9175 |
+| 0.1393        | 9.0   | 801  | 0.7502          | 0.8870   | 0.8990 | 0.8812    | 0.9175 |
+| 0.1393        | 10.0  | 890  | 0.7642          | 0.8870   | 0.8990 | 0.8812    | 0.9175 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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runs/Jan13_08-12-54_51b350982aae/events.out.tfevents.1705134010.51b350982aae.893.1

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