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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: bert-base-uncased |
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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: finetuned-bert-mrpc |
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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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# finetuned-bert-mrpc |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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: 0.4725 |
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- Accuracy: 0.8382 |
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- F1: 0.8881 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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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- mixed_precision_training: Native AMP |
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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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| 0.5236 | 0.4348 | 50 | 0.4882 | 0.7647 | 0.8452 | |
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| 0.4277 | 0.8696 | 100 | 0.3845 | 0.8431 | 0.8940 | |
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| 0.2727 | 1.3043 | 150 | 0.3824 | 0.8529 | 0.8980 | |
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| 0.2285 | 1.7391 | 200 | 0.3646 | 0.8358 | 0.8831 | |
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| 0.1305 | 2.1739 | 250 | 0.3605 | 0.8652 | 0.9002 | |
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| 0.1193 | 2.6087 | 300 | 0.4725 | 0.8382 | 0.8881 | |
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### Framework versions |
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- Transformers 4.52.4 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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