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--- |
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license: apache-2.0 |
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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: distilbert-base-uncased-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: 0.5474713423103301 |
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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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# distilbert-base-uncased-cola |
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This model is a fine-tuned version of [sciarrilli/distilbert-base-uncased-cola](https://huggingface.co/sciarrilli/distilbert-base-uncased-cola) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2934 |
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- Matthews Correlation: 0.5475 |
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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: 10 |
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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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| 0.3525 | 1.0 | 535 | 0.5328 | 0.4268 | |
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| 0.2941 | 2.0 | 1070 | 0.6235 | 0.4805 | |
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| 0.2111 | 3.0 | 1605 | 0.6743 | 0.4982 | |
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| 0.1607 | 4.0 | 2140 | 0.7463 | 0.5172 | |
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| 0.1487 | 5.0 | 2675 | 0.9553 | 0.4935 | |
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| 0.102 | 6.0 | 3210 | 1.0206 | 0.5121 | |
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| 0.0878 | 7.0 | 3745 | 1.1293 | 0.5347 | |
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| 0.0605 | 8.0 | 4280 | 1.1958 | 0.5422 | |
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| 0.0418 | 9.0 | 4815 | 1.2673 | 0.5449 | |
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| 0.0378 | 10.0 | 5350 | 1.2934 | 0.5475 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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