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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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- f1 |
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model-index: |
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- name: roberta-large-csb_1 |
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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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# roberta-large-csb_1 |
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2773 |
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- Accuracy: 0.9011 |
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- F1: 0.9010 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.5696 | 1.0 | 57 | 0.3749 | 0.8308 | 0.8307 | |
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| 0.3637 | 2.0 | 114 | 0.2749 | 0.8813 | 0.8812 | |
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| 0.3087 | 3.0 | 171 | 0.2479 | 0.8813 | 0.8813 | |
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| 0.2497 | 4.0 | 228 | 0.2415 | 0.8923 | 0.8919 | |
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| 0.2025 | 5.0 | 285 | 0.2773 | 0.9011 | 0.9010 | |
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| 0.1521 | 6.0 | 342 | 0.3194 | 0.8791 | 0.8790 | |
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| 0.1251 | 7.0 | 399 | 0.4850 | 0.8681 | 0.8664 | |
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| 0.0496 | 8.0 | 456 | 0.5794 | 0.8725 | 0.8710 | |
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| 0.0241 | 9.0 | 513 | 0.5833 | 0.8747 | 0.8738 | |
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| 0.0221 | 10.0 | 570 | 0.6399 | 0.8725 | 0.8713 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.2.1 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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