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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-reddit-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-reddit-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: 0.9796 |
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- Accuracy: 0.7881 |
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- F1: 0.5335 |
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- Precision: 0.5938 |
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- Recall: 0.4844 |
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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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| 0.4385 | 1.0 | 309 | 0.4258 | 0.7980 | 0.5675 | 0.6111 | 0.5297 | |
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| 0.3451 | 2.0 | 618 | 0.4345 | 0.8030 | 0.6283 | 0.5949 | 0.6657 | |
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| 0.2404 | 3.0 | 927 | 0.5054 | 0.8016 | 0.5318 | 0.6490 | 0.4504 | |
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| 0.1326 | 4.0 | 1236 | 0.7033 | 0.7860 | 0.5452 | 0.5820 | 0.5127 | |
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| 0.0787 | 5.0 | 1545 | 0.9796 | 0.7881 | 0.5335 | 0.5938 | 0.4844 | |
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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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