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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 |
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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 |
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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: 0.2625 |
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- Accuracy: 0.8857 |
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- F1: 0.8860 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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| 0.3718 | 1.0 | 228 | 0.2774 | 0.8747 | 0.8748 | |
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| 0.3126 | 2.0 | 456 | 0.2625 | 0.8857 | 0.8860 | |
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| 0.2053 | 3.0 | 684 | 0.3058 | 0.8791 | 0.8787 | |
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| 0.1797 | 4.0 | 912 | 0.4676 | 0.8615 | 0.8601 | |
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| 0.1087 | 5.0 | 1140 | 0.8824 | 0.8330 | 0.8288 | |
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| 0.0827 | 6.0 | 1368 | 0.9341 | 0.8637 | 0.8616 | |
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| 0.0336 | 7.0 | 1596 | 0.9355 | 0.8571 | 0.8552 | |
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| 0.0077 | 8.0 | 1824 | 0.9166 | 0.8725 | 0.8720 | |
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| 0.0011 | 9.0 | 2052 | 0.9783 | 0.8747 | 0.8740 | |
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| 0.0001 | 10.0 | 2280 | 1.0445 | 0.8703 | 0.8692 | |
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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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