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--- |
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library_name: transformers |
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language: |
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- en |
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license: apache-2.0 |
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base_model: google/bert_uncased_L-4_H-256_A-4 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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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: bert_uncased_L-4_H-256_A-4_qqp |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE QQP |
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type: glue |
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args: qqp |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8774672273064557 |
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- name: F1 |
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type: f1 |
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value: 0.8326577489528443 |
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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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# bert_uncased_L-4_H-256_A-4_qqp |
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This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2840 |
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- Accuracy: 0.8775 |
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- F1: 0.8327 |
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- Combined Score: 0.8551 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.3985 | 1.0 | 1422 | 0.3341 | 0.8486 | 0.7966 | 0.8226 | |
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| 0.3199 | 2.0 | 2844 | 0.3058 | 0.8636 | 0.8245 | 0.8440 | |
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| 0.2819 | 3.0 | 4266 | 0.2883 | 0.8732 | 0.8341 | 0.8536 | |
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| 0.2525 | 4.0 | 5688 | 0.2840 | 0.8775 | 0.8327 | 0.8551 | |
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| 0.2304 | 5.0 | 7110 | 0.2858 | 0.8808 | 0.8448 | 0.8628 | |
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| 0.2094 | 6.0 | 8532 | 0.2877 | 0.8817 | 0.8450 | 0.8633 | |
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| 0.1912 | 7.0 | 9954 | 0.2909 | 0.8823 | 0.8462 | 0.8642 | |
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| 0.1749 | 8.0 | 11376 | 0.2944 | 0.8856 | 0.8512 | 0.8684 | |
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| 0.1604 | 9.0 | 12798 | 0.3125 | 0.8863 | 0.8526 | 0.8694 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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