| license: apache-2.0 | |
| tags: | |
| - text-classification | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: distilroberta-base | |
| model-index: | |
| - name: platzi-distilroberta-base-mrpc-glue-luigitercero | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: datasetX | |
| type: glue | |
| config: mrpc | |
| split: validation | |
| args: mrpc | |
| metrics: | |
| - type: accuracy | |
| value: 0.8431372549019608 | |
| name: Accuracy | |
| - type: f1 | |
| value: 0.8836363636363636 | |
| name: F1 | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # platzi-distilroberta-base-mrpc-glue-luigitercero | |
| This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the datasetX dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.6591 | |
| - Accuracy: 0.8431 | |
| - F1: 0.8836 | |
| ## 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 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.1853 | 1.09 | 500 | 0.6591 | 0.8431 | 0.8836 | | |
| | 0.1812 | 2.18 | 1000 | 0.6591 | 0.8431 | 0.8836 | | |
| ### Framework versions | |
| - Transformers 4.26.1 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.13.2 | |