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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-uncased |
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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: CS221-bert-base-uncased-finetuned-semeval-NT-sun |
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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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# CS221-bert-base-uncased-finetuned-semeval-NT-sun |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4060 |
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- F1: 0.6852 |
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- Roc Auc: 0.7739 |
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- Accuracy: 0.5135 |
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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: 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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| 0.4264 | 1.0 | 93 | 0.4356 | 0.6154 | 0.7316 | 0.4811 | |
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| 0.3577 | 2.0 | 186 | 0.3867 | 0.6667 | 0.7663 | 0.4811 | |
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| 0.321 | 3.0 | 279 | 0.3666 | 0.6773 | 0.7702 | 0.4973 | |
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| 0.2953 | 4.0 | 372 | 0.3691 | 0.6698 | 0.7625 | 0.4973 | |
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| 0.236 | 5.0 | 465 | 0.3840 | 0.6667 | 0.7645 | 0.4757 | |
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| 0.2011 | 6.0 | 558 | 0.4060 | 0.6852 | 0.7739 | 0.5135 | |
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| 0.1135 | 7.0 | 651 | 0.4200 | 0.6711 | 0.7690 | 0.4865 | |
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| 0.1056 | 8.0 | 744 | 0.4691 | 0.6636 | 0.7607 | 0.4973 | |
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| 0.0854 | 9.0 | 837 | 0.4758 | 0.6727 | 0.7680 | 0.5027 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Tokenizers 0.21.0 |
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