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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-2_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-2_H-256_A-4_mrpc |
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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 MRPC |
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type: glue |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7475490196078431 |
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- name: F1 |
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type: f1 |
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value: 0.835725677830941 |
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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-2_H-256_A-4_mrpc |
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-256_A-4](https://huggingface.co/google/bert_uncased_L-2_H-256_A-4) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5344 |
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- Accuracy: 0.7475 |
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- F1: 0.8357 |
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- Combined Score: 0.7916 |
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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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| 0.619 | 1.0 | 15 | 0.5956 | 0.6887 | 0.8146 | 0.7517 | |
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| 0.5893 | 2.0 | 30 | 0.5835 | 0.7010 | 0.8179 | 0.7594 | |
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| 0.5612 | 3.0 | 45 | 0.5597 | 0.7059 | 0.8171 | 0.7615 | |
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| 0.5397 | 4.0 | 60 | 0.5398 | 0.7377 | 0.8320 | 0.7849 | |
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| 0.5063 | 5.0 | 75 | 0.5358 | 0.7426 | 0.8336 | 0.7881 | |
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| 0.476 | 6.0 | 90 | 0.5344 | 0.7475 | 0.8357 | 0.7916 | |
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| 0.4361 | 7.0 | 105 | 0.5515 | 0.7451 | 0.8349 | 0.7900 | |
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| 0.4014 | 8.0 | 120 | 0.5508 | 0.75 | 0.8365 | 0.7933 | |
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| 0.3684 | 9.0 | 135 | 0.5901 | 0.7304 | 0.8254 | 0.7779 | |
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| 0.3396 | 10.0 | 150 | 0.5755 | 0.7426 | 0.8276 | 0.7851 | |
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| 0.3061 | 11.0 | 165 | 0.5943 | 0.75 | 0.8317 | 0.7908 | |
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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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