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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/roberta-large |
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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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model-index: |
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- name: fine_tuned_super_clean_raid |
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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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# fine_tuned_super_clean_raid |
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0885 |
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- Accuracy: 0.9715 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.3162 | 0.0196 | 100 | 0.2046 | 0.9306 | |
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| 0.2626 | 0.0393 | 200 | 0.2988 | 0.9129 | |
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| 0.2888 | 0.0589 | 300 | 0.2148 | 0.9490 | |
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| 0.217 | 0.0786 | 400 | 0.1970 | 0.9523 | |
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| 0.2201 | 0.0982 | 500 | 0.1533 | 0.9596 | |
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| 0.2836 | 0.1178 | 600 | 0.1406 | 0.9563 | |
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| 0.2196 | 0.1375 | 700 | 0.1326 | 0.9574 | |
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| 0.1669 | 0.1571 | 800 | 0.1549 | 0.9622 | |
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| 0.1482 | 0.1767 | 900 | 0.1740 | 0.9629 | |
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| 0.1997 | 0.1964 | 1000 | 0.0885 | 0.9715 | |
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| 0.1271 | 0.2160 | 1100 | 0.4294 | 0.9163 | |
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| 0.1754 | 0.2357 | 1200 | 0.1268 | 0.9567 | |
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| 0.1479 | 0.2553 | 1300 | 0.3952 | 0.9328 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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