--- library_name: transformers license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola results: [] --- # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8036 - Matthews Correlation: 0.5495 ## 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: Use OptimizerNames.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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.5201 | 1.0 | 535 | 0.4638 | 0.4527 | | 0.3502 | 2.0 | 1070 | 0.4823 | 0.5474 | | 0.234 | 3.0 | 1605 | 0.6158 | 0.5182 | | 0.1686 | 4.0 | 2140 | 0.7848 | 0.5323 | | 0.1276 | 5.0 | 2675 | 0.8036 | 0.5495 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.6.0+cu124 - Datasets 3.4.1 - Tokenizers 0.21.1