--- library_name: transformers language: - en base_model: gokulsrinivasagan/distilbert_lda_50_v1_book tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation - accuracy model-index: - name: distilbert_lda_50_v1_book_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: 0.2814348686899425 - name: Accuracy type: accuracy value: 0.7286673188209534 --- # distilbert_lda_50_v1_book_cola This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_50_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1_book) on the GLUE COLA dataset. It achieves the following results on the evaluation set: - Loss: 0.5675 - Matthews Correlation: 0.2814 - Accuracy: 0.7287 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| | 0.6101 | 1.0 | 34 | 0.6117 | 0.0 | 0.6913 | | 0.5905 | 2.0 | 68 | 0.5881 | 0.1359 | 0.7009 | | 0.5141 | 3.0 | 102 | 0.5675 | 0.2814 | 0.7287 | | 0.4056 | 4.0 | 136 | 0.6507 | 0.2830 | 0.7296 | | 0.3156 | 5.0 | 170 | 0.6659 | 0.3282 | 0.7411 | | 0.2415 | 6.0 | 204 | 0.7348 | 0.3457 | 0.7469 | | 0.1867 | 7.0 | 238 | 0.6643 | 0.3566 | 0.7421 | | 0.1608 | 8.0 | 272 | 0.6997 | 0.3558 | 0.7335 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.2.1+cu118 - Datasets 2.17.0 - Tokenizers 0.20.3