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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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- f1 |
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- accuracy |
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model-index: |
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- name: roberta-large-finetuned-augmentation-LUNAR-TAPT-macro |
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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-finetuned-augmentation-LUNAR-TAPT-macro |
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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: 0.2832 |
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- F1: 0.8635 |
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- Roc Auc: 0.8937 |
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- Accuracy: 0.7150 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.2744 | 1.0 | 421 | 0.2710 | 0.7932 | 0.8326 | 0.5754 | |
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| 0.2287 | 2.0 | 842 | 0.2281 | 0.8454 | 0.8815 | 0.6758 | |
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| 0.1678 | 3.0 | 1263 | 0.2293 | 0.8563 | 0.8879 | 0.7049 | |
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| 0.1287 | 4.0 | 1684 | 0.2491 | 0.8619 | 0.8918 | 0.7126 | |
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| 0.1298 | 5.0 | 2105 | 0.2591 | 0.8633 | 0.8936 | 0.7173 | |
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| 0.0788 | 6.0 | 2526 | 0.2703 | 0.8612 | 0.8914 | 0.7138 | |
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| 0.0883 | 7.0 | 2947 | 0.2679 | 0.8605 | 0.8905 | 0.7203 | |
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| 0.0821 | 8.0 | 3368 | 0.2832 | 0.8635 | 0.8937 | 0.7150 | |
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| 0.0739 | 9.0 | 3789 | 0.2998 | 0.8601 | 0.8963 | 0.7156 | |
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| 0.0538 | 10.0 | 4210 | 0.2951 | 0.8615 | 0.8957 | 0.7167 | |
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| 0.0466 | 11.0 | 4631 | 0.2999 | 0.8626 | 0.8976 | 0.7126 | |
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| 0.0657 | 12.0 | 5052 | 0.3060 | 0.8608 | 0.8976 | 0.7203 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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