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--- |
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license: mit |
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base_model: indobenchmark/indobert-base-p1 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: indobert-base-p1-twitter-indonesia-sarcastic |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# indobert-base-p1-twitter-indonesia-sarcastic |
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This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8125 |
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- Accuracy: 0.8662 |
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- F1: 0.7273 |
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- Precision: 0.7385 |
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- Recall: 0.7164 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5101 | 1.0 | 59 | 0.4221 | 0.7836 | 0.6081 | 0.5556 | 0.6716 | |
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| 0.3508 | 2.0 | 118 | 0.3479 | 0.8246 | 0.6713 | 0.6316 | 0.7164 | |
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| 0.221 | 3.0 | 177 | 0.3511 | 0.8582 | 0.6935 | 0.7544 | 0.6418 | |
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| 0.1157 | 4.0 | 236 | 0.4352 | 0.8396 | 0.6861 | 0.6714 | 0.7015 | |
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| 0.0453 | 5.0 | 295 | 0.6923 | 0.8582 | 0.7077 | 0.7302 | 0.6866 | |
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| 0.0192 | 6.0 | 354 | 0.7378 | 0.8694 | 0.7287 | 0.7581 | 0.7015 | |
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| 0.0159 | 7.0 | 413 | 0.8860 | 0.8545 | 0.6723 | 0.7692 | 0.5970 | |
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| 0.0165 | 8.0 | 472 | 0.8261 | 0.8694 | 0.7445 | 0.7286 | 0.7612 | |
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| 0.0175 | 9.0 | 531 | 0.8732 | 0.8731 | 0.7424 | 0.7538 | 0.7313 | |
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| 0.0062 | 10.0 | 590 | 0.9648 | 0.8657 | 0.7273 | 0.7385 | 0.7164 | |
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| 0.0003 | 11.0 | 649 | 1.0108 | 0.8619 | 0.7176 | 0.7344 | 0.7015 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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