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--- |
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language: |
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- en |
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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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widget: |
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- text: The cat sat on the mat. |
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example_title: Correct grammatical sentence |
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- text: Me and my friend going to the store. |
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example_title: Incorrect subject-verb agreement |
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- text: I ain't got no money. |
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example_title: Incorrect verb conjugation and double negative |
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- text: She don't like pizza no more. |
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example_title: Incorrect verb conjugation and double negative |
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- text: They is arriving tomorrow. |
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example_title: Incorrect verb conjugation |
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base_model: microsoft/deberta-v3-xsmall |
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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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type: text-classification |
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name: Text Classification |
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dataset: |
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name: GLUE COLA |
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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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- type: matthews_correlation |
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value: 0.5894856058137782 |
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name: Matthews Correlation |
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--- |
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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 COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4237 |
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- Matthews Correlation: 0.5895 |
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## Model description |
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Trying to find a decent optimum between accuracy/quality and inference speed. |
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```json |
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{ |
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"epoch": 3.0, |
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"eval_loss": 0.423, |
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"eval_matthews_correlation": 0.589, |
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"eval_runtime": 5.0422, |
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"eval_samples": 1043, |
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"eval_samples_per_second": 206.853, |
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"eval_steps_per_second": 51.763 |
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} |
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``` |
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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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