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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-128_A-2 |
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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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- matthews_correlation |
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- accuracy |
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model-index: |
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- name: bert_uncased_L-2_H-128_A-2_cola |
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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 COLA |
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type: glue |
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args: cola |
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metrics: |
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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.00286100001416597 |
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- name: Accuracy |
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type: accuracy |
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value: 0.690316379070282 |
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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-128_A-2_cola |
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the GLUE COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6155 |
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- Matthews Correlation: 0.0029 |
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- Accuracy: 0.6903 |
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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 | Matthews Correlation | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| |
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| 0.6288 | 1.0 | 34 | 0.6191 | 0.0 | 0.6913 | |
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| 0.6087 | 2.0 | 68 | 0.6184 | 0.0 | 0.6913 | |
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| 0.6076 | 3.0 | 102 | 0.6176 | 0.0 | 0.6913 | |
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| 0.6066 | 4.0 | 136 | 0.6169 | 0.0 | 0.6913 | |
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| 0.605 | 5.0 | 170 | 0.6170 | 0.0 | 0.6913 | |
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| 0.6018 | 6.0 | 204 | 0.6164 | 0.0 | 0.6913 | |
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| 0.5976 | 7.0 | 238 | 0.6163 | 0.0 | 0.6913 | |
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| 0.5871 | 8.0 | 272 | 0.6159 | 0.0464 | 0.6922 | |
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| 0.5824 | 9.0 | 306 | 0.6155 | 0.0029 | 0.6903 | |
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| 0.5711 | 10.0 | 340 | 0.6198 | 0.0198 | 0.6702 | |
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| 0.5591 | 11.0 | 374 | 0.6221 | 0.0685 | 0.6721 | |
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| 0.5496 | 12.0 | 408 | 0.6284 | 0.1240 | 0.6702 | |
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| 0.5397 | 13.0 | 442 | 0.6350 | 0.1096 | 0.6548 | |
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| 0.529 | 14.0 | 476 | 0.6423 | 0.0951 | 0.6433 | |
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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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