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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: deberta-base-mnli-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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metrics: |
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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.6281691768918801 |
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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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# deberta-base-mnli-finetuned-cola |
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This model is a fine-tuned version of [microsoft/deberta-base-mnli](https://huggingface.co/microsoft/deberta-base-mnli) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8205 |
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- Matthews Correlation: 0.6282 |
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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: 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: 5 |
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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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| 0.4713 | 1.0 | 535 | 0.5110 | 0.5797 | |
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| 0.2678 | 2.0 | 1070 | 0.6648 | 0.5154 | |
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| 0.1811 | 3.0 | 1605 | 0.6681 | 0.6121 | |
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| 0.113 | 4.0 | 2140 | 0.8205 | 0.6282 | |
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| 0.0831 | 5.0 | 2675 | 1.0413 | 0.6057 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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