--- license: apache-2.0 tags: - generated_from_trainer datasets: - nyu-mll/glue metrics: - matthews_correlation model_index: - name: distilbert-base-uncased-finetuned-cola results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue args: cola metric: name: Matthews Correlation type: matthews_correlation value: 0.5526838482765232 --- # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.7691 - Matthews Correlation: 0.5527 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.5247 | 1.0 | 535 | 0.5390 | 0.4315 | | 0.353 | 2.0 | 1070 | 0.5273 | 0.4994 | | 0.2386 | 3.0 | 1605 | 0.6391 | 0.5089 | | 0.17 | 4.0 | 2140 | 0.7691 | 0.5527 | | 0.1348 | 5.0 | 2675 | 0.8483 | 0.5472 | ### Framework versions - Transformers 4.9.2 - Pytorch 1.9.0+cu102 - Datasets 1.11.0 - Tokenizers 0.10.3