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README.md
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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-v3-xsmall-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: 0.5794528111058918
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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-xsmall-CoLA
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This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4636
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- Matthews Correlation: 0.5795
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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: 6e-05
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- train_batch_size: 32
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- eval_batch_size: 4
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- seed: 16105
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 3.0
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- mixed_precision_training: Native AMP
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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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| 0.3945 | 1.0 | 67 | 0.4323 | 0.5778 |
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| 0.3214 | 2.0 | 134 | 0.4237 | 0.5895 |
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| 0.3059 | 3.0 | 201 | 0.4636 | 0.5795 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.1
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