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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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- matthews_correlation |
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- accuracy |
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model-index: |
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- name: bert_uncased_L-4_H-256_A-4_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: 0.2650812590803394 |
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- name: Accuracy |
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type: accuracy |
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value: 0.7027804255485535 |
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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_cola |
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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 COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5943 |
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- Matthews Correlation: 0.2651 |
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- Accuracy: 0.7028 |
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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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| 0.6358 | 1.0 | 34 | 0.6182 | 0.0 | 0.6913 | |
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| 0.6077 | 2.0 | 68 | 0.6184 | 0.0 | 0.6913 | |
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| 0.5982 | 3.0 | 102 | 0.6035 | 0.0 | 0.6913 | |
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| 0.575 | 4.0 | 136 | 0.5997 | 0.1458 | 0.7009 | |
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| 0.5391 | 5.0 | 170 | 0.5992 | 0.2018 | 0.7028 | |
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| 0.4999 | 6.0 | 204 | 0.6159 | 0.2088 | 0.7085 | |
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| 0.4722 | 7.0 | 238 | 0.5974 | 0.2782 | 0.7248 | |
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| 0.4437 | 8.0 | 272 | 0.5943 | 0.2651 | 0.7028 | |
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| 0.4204 | 9.0 | 306 | 0.6239 | 0.2618 | 0.7210 | |
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| 0.3956 | 10.0 | 340 | 0.6360 | 0.2655 | 0.7191 | |
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| 0.3671 | 11.0 | 374 | 0.6876 | 0.2592 | 0.7200 | |
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| 0.3546 | 12.0 | 408 | 0.7041 | 0.2665 | 0.7239 | |
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| 0.333 | 13.0 | 442 | 0.6849 | 0.2891 | 0.7229 | |
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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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