--- license: apache-2.0 base_model: distilroberta-base tags: - text-classification - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: platzi-distilroberta-base-mrpc-glue-djps10 results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue config: mrpc split: validation args: mrpc metrics: - name: Accuracy type: accuracy value: 0.7965686274509803 - name: F1 type: f1 value: 0.8672 --- # platzi-distilroberta-base-mrpc-glue-djps10 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.4939 - Accuracy: 0.7966 - F1: 0.8672 ## 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: 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 | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.5453 | 1.09 | 500 | 0.4939 | 0.7966 | 0.8672 | | 0.3506 | 2.18 | 1000 | 0.7823 | 0.8186 | 0.8693 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.3 - Tokenizers 0.13.3