--- license: apache-2.0 tags: - text-classification - generated_from_trainer datasets: - glue metrics: - accuracy - f1 widget: - text: - >- Yucaipa owned Dominick 's before selling the chain to Safeway in 1998 for $ 2.5 billion. - >- Yucaipa bought Dominick's in 1995 for $ 693 million and sold it to Safeway for $ 1.8 billion in 1998. example_title: Not Equivalent - text: - >- According to the federal Centers for Disease Control and Prevention ( news - web sites ) , there were 19 reported cases of measles in the United States in 2002. - >- The Centers for Disease Control and Prevention said there were 19 reported cases of measles in the United States in 2002. example_title: Equivalent model-index: - name: platzi-distilroberta-base-mrpc-glue 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: 0.8627450980392157 - name: F1 type: f1 value: 0.9 --- # platzi-distilroberta-base-mrpc-glue This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue and the mrpc datasets. It achieves the following results on the evaluation set: - Loss: 0.4414 - Accuracy: 0.8627 - F1: 0.9 ## 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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.5624 | 1.09 | 500 | 0.4727 | 0.7990 | 0.8591 | | 0.4063 | 2.18 | 1000 | 0.4414 | 0.8627 | 0.9 | | 0.2612 | 3.27 | 1500 | 0.5972 | 0.8529 | 0.8986 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu116 - Datasets 2.9.0 - Tokenizers 0.13.2