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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: model |
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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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# model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7669 |
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- Precision: 0.2852 |
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- Recall: 0.2420 |
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- F1: 0.2618 |
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- Accuracy: 0.8806 |
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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: 4 |
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- eval_batch_size: 4 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0387 | 0.4292 | 100 | 3.2626 | 0.2781 | 0.2316 | 0.2527 | 0.8801 | |
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| 0.0432 | 0.8584 | 200 | 4.3510 | 0.3575 | 0.1485 | 0.2098 | 0.9021 | |
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| 0.0305 | 1.2876 | 300 | 4.4340 | 0.3663 | 0.1578 | 0.2206 | 0.9024 | |
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| 0.0303 | 1.7167 | 400 | 4.2810 | 0.3418 | 0.1537 | 0.2120 | 0.9000 | |
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| 0.0347 | 2.1459 | 500 | 4.3217 | 0.3607 | 0.1828 | 0.2426 | 0.9001 | |
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| 0.0235 | 2.5751 | 600 | 4.3738 | 0.3302 | 0.1817 | 0.2344 | 0.8961 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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