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README.md
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---
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license: mit
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base_model: microsoft/deberta-v3-base
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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-v3-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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config: cola
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split: validation
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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: 0.6932783112452325
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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-v3-base-finetuned-cola
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6510
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- Matthews Correlation: 0.6933
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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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| 0.3853 | 1.0 | 535 | 0.3907 | 0.6307 |
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| 0.2186 | 2.0 | 1070 | 0.5065 | 0.6603 |
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| 0.1481 | 3.0 | 1605 | 0.5638 | 0.6740 |
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| 0.1002 | 4.0 | 2140 | 0.6510 | 0.6933 |
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| 0.0656 | 5.0 | 2675 | 0.7462 | 0.6877 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.1
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- Tokenizers 0.13.3
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