--- library_name: transformers language: - en license: apache-2.0 base_model: google/bert_uncased_L-4_H-512_A-8 tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation - accuracy model-index: - name: bert_uncased_L-4_H-512_A-8_cola results: - task: name: Text Classification type: text-classification dataset: name: GLUE COLA type: glue args: cola metrics: - name: Matthews Correlation type: matthews_correlation value: 0.25880032134413367 - name: Accuracy type: accuracy value: 0.7248322367668152 --- # bert_uncased_L-4_H-512_A-8_cola This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the GLUE COLA dataset. It achieves the following results on the evaluation set: - Loss: 0.5796 - Matthews Correlation: 0.2588 - Accuracy: 0.7248 ## 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: 5e-05 - train_batch_size: 256 - eval_batch_size: 256 - seed: 10 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| | 0.6069 | 1.0 | 34 | 0.6018 | 0.0 | 0.6913 | | 0.5619 | 2.0 | 68 | 0.5891 | 0.1766 | 0.7076 | | 0.4858 | 3.0 | 102 | 0.5796 | 0.2588 | 0.7248 | | 0.4109 | 4.0 | 136 | 0.6467 | 0.2838 | 0.7306 | | 0.349 | 5.0 | 170 | 0.6379 | 0.3133 | 0.7354 | | 0.294 | 6.0 | 204 | 0.6805 | 0.3436 | 0.7440 | | 0.2564 | 7.0 | 238 | 0.7498 | 0.3178 | 0.7363 | | 0.2222 | 8.0 | 272 | 0.7861 | 0.3320 | 0.7383 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.2.1+cu118 - Datasets 2.17.0 - Tokenizers 0.20.3