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--- |
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license: apache-2.0 |
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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: navid_test_bert |
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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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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: 0.5834463254140851 |
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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 |
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type: glue |
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config: cola |
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split: validation |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8312559923298178 |
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verified: true |
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- name: Precision |
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type: precision |
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value: 0.8376703841387856 |
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verified: true |
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- name: Recall |
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type: recall |
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value: 0.9375866851595007 |
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verified: true |
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- name: AUC |
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type: auc |
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value: 0.8870185473936304 |
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verified: true |
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- name: F1 |
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type: f1 |
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value: 0.8848167539267016 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.815069854259491 |
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verified: true |
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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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# navid_test_bert |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co./bert-base-cased) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8149 |
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- Matthews Correlation: 0.5834 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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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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| 0.4598 | 1.0 | 1069 | 0.4919 | 0.5314 | |
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| 0.3228 | 2.0 | 2138 | 0.6362 | 0.5701 | |
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| 0.17 | 3.0 | 3207 | 0.8149 | 0.5834 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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