End of training
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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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metrics:
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- matthews_correlation
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model-index:
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- name: deberta-v3-base-finetuned-cola-midterm
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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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# deberta-v3-base-finetuned-cola-midterm
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4382
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- Matthews Correlation: 0.6943
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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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| 0.3901 | 1.0 | 535 | 0.3711 | 0.6257 |
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| 0.2265 | 2.0 | 1070 | 0.4382 | 0.6943 |
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| 0.1535 | 3.0 | 1605 | 0.6309 | 0.6652 |
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| 0.0953 | 4.0 | 2140 | 0.7058 | 0.6774 |
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| 0.0686 | 5.0 | 2675 | 0.6853 | 0.6924 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.17.1
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- Tokenizers 0.15.2
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