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--- |
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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: mobilebert_sa_GLUE_Experiment_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: train |
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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: 0.09007205990892461 |
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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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# mobilebert_sa_GLUE_Experiment_cola |
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This model is a fine-tuned version of [](https://huggingface.co/) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6893 |
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- Matthews Correlation: 0.0901 |
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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: 5e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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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: linear |
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- num_epochs: 50 |
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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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| 0.6197 | 1.0 | 34 | 0.6239 | 0.0 | |
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| 0.6078 | 2.0 | 68 | 0.6179 | 0.0 | |
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| 0.6064 | 3.0 | 102 | 0.6180 | 0.0 | |
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| 0.6073 | 4.0 | 136 | 0.6176 | 0.0 | |
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| 0.6069 | 5.0 | 170 | 0.6173 | 0.0 | |
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| 0.6043 | 6.0 | 204 | 0.6166 | 0.0 | |
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| 0.6004 | 7.0 | 238 | 0.6131 | 0.0 | |
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| 0.5842 | 8.0 | 272 | 0.6241 | 0.0951 | |
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| 0.5192 | 9.0 | 306 | 0.6362 | 0.0598 | |
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| 0.4884 | 10.0 | 340 | 0.7010 | 0.0801 | |
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| 0.4559 | 11.0 | 374 | 0.6731 | 0.0905 | |
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| 0.4367 | 12.0 | 408 | 0.6893 | 0.0901 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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