--- license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation model-index: - name: navid_test_bert results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue args: cola metrics: - name: Matthews Correlation type: matthews_correlation value: 0.5834463254140851 - task: type: text-classification name: Text Classification dataset: name: glue type: glue config: cola split: validation metrics: - name: Accuracy type: accuracy value: 0.8312559923298178 verified: true - name: Precision type: precision value: 0.8376703841387856 verified: true - name: Recall type: recall value: 0.9375866851595007 verified: true - name: AUC type: auc value: 0.8870185473936304 verified: true - name: F1 type: f1 value: 0.8848167539267016 verified: true - name: loss type: loss value: 0.815069854259491 verified: true --- # navid_test_bert This model is a fine-tuned version of [bert-base-cased](https://huggingface.co./bert-base-cased) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.8149 - Matthews Correlation: 0.5834 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.4598 | 1.0 | 1069 | 0.4919 | 0.5314 | | 0.3228 | 2.0 | 2138 | 0.6362 | 0.5701 | | 0.17 | 3.0 | 3207 | 0.8149 | 0.5834 | ### Framework versions - Transformers 4.16.2 - Pytorch 1.10.0+cu111 - Datasets 1.18.2 - Tokenizers 0.11.0