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--- |
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license: mit |
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base_model: gpt2 |
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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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- recall |
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- precision |
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model-index: |
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- name: gpt2-text-classification-v2 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/date3k2/gpt2-text-classification/runs/52an6tu1) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/date3k2/gpt2-text-classification/runs/lu5o1szk) |
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# gpt2-text-classification-v2 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2002 |
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- Accuracy: 0.9342 |
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- F1: 0.9340 |
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- Recall: 0.9314 |
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- Precision: 0.9367 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall | |
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|:-------------:|:------:|:----:|:--------:|:------:|:---------------:|:---------:|:------:| |
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| 0.327 | 0.9974 | 260 | 0.8973 | 0.8929 | 0.2559 | 0.9333 | 0.8558 | |
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| 0.241 | 1.9987 | 521 | 0.919 | 0.9180 | 0.2039 | 0.9296 | 0.9066 | |
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| 0.244 | 3.0 | 782 | 0.9154 | 0.9192 | 0.2156 | 0.8799 | 0.9621 | |
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| 0.1843 | 3.9974 | 1042 | 0.9299 | 0.9288 | 0.1888 | 0.9427 | 0.9154 | |
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| 0.1608 | 4.9987 | 1303 | 0.9301 | 0.9291 | 0.1855 | 0.9428 | 0.9158 | |
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| 0.124 | 6.0 | 1564 | 0.9322 | 0.9319 | 0.1826 | 0.9357 | 0.9282 | |
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| 0.112 | 6.9974 | 1820 | 0.2099 | 0.9315 | 0.9303 | 0.9138 | 0.9473 | |
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| 0.0903 | 7.9987 | 2081 | 0.2002 | 0.9342 | 0.9340 | 0.9314 | 0.9367 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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