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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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--- |
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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: 0.4497 |
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- Matthews Correlation: 0.6272 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: IPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 20 |
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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 precision: Mixed Precision |
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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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| 0.4453 | 1.0 | 133 | 0.4348 | 0.5391 | |
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| 0.3121 | 2.0 | 266 | 0.3938 | 0.5827 | |
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| 0.1149 | 3.0 | 399 | 0.4497 | 0.6272 | |
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| 0.1194 | 4.0 | 532 | 0.5005 | 0.6076 | |
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| 0.1639 | 5.0 | 665 | 0.5645 | 0.5943 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cpu |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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