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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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model-index: |
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- name: xtremedistil-l12-h384-uncased-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 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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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.5395539646127814 |
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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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--- |
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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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# xtremedistil-l12-h384-uncased-CoLA |
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This model is a fine-tuned version of [microsoft/xtremedistil-l12-h384-uncased](https://huggingface.co/microsoft/xtremedistil-l12-h384-uncased) on the GLUE COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4974 |
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- Matthews Correlation: 0.5396 |
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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: 0.0001 |
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- train_batch_size: 128 |
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- eval_batch_size: 16 |
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- seed: 5559 |
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- distributed_type: multi-GPU |
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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: 16.0 |
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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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| 0.4822 | 1.0 | 67 | 0.5893 | 0.2621 | |
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| 0.4669 | 2.0 | 134 | 0.5811 | 0.3722 | |
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| 0.3077 | 3.0 | 201 | 0.6150 | 0.4383 | |
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| 0.2594 | 4.0 | 268 | 0.4974 | 0.5396 | |
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| 0.21 | 5.0 | 335 | 0.5594 | 0.5182 | |
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| 0.1526 | 6.0 | 402 | 0.5715 | 0.5150 | |
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| 0.1775 | 7.0 | 469 | 0.6637 | 0.5020 | |
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| 0.1681 | 8.0 | 536 | 0.6958 | 0.5131 | |
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| 0.124 | 9.0 | 603 | 0.7057 | 0.5154 | |
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| 0.1111 | 10.0 | 670 | 0.8173 | 0.5074 | |
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| 0.1332 | 11.0 | 737 | 0.8253 | 0.5260 | |
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| 0.0673 | 12.0 | 804 | 0.8086 | 0.5180 | |
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| 0.0512 | 13.0 | 871 | 0.8409 | 0.5128 | |
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| 0.0457 | 14.0 | 938 | 0.8760 | 0.4947 | |
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| 0.04 | 15.0 | 1005 | 0.8522 | 0.5103 | |
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| 0.0485 | 16.0 | 1072 | 0.8556 | 0.5076 | |
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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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