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--- |
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license: mit |
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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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model_index: |
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- name: roberta-base-finetuned-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 |
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type: glue |
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args: cola |
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metric: |
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name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.557882735147727 |
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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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# roberta-base-finetuned-cola |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4716 |
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- Matthews Correlation: 0.5579 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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```python |
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from transformers import AutoModelForSequenceClassification |
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model = AutoModelForSequenceClassification.from_pretrained("jxuhf/roberta-base-finetuned-cola") |
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``` |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:| |
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| 0.4981 | 1.0 | 535 | 0.5162 | 0.5081 | |
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| 0.314 | 2.0 | 1070 | 0.4716 | 0.5579 | |
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### Framework versions |
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- Transformers 4.9.0 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.10.2 |
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- Tokenizers 0.10.3 |
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