--- tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: squeezebert-mnli-headless-finetuned-mrpc 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: 0.8823529411764706 - name: F1 type: f1 value: 0.9136690647482014 --- # squeezebert-mnli-headless-finetuned-mrpc This model is a fine-tuned version of [squeezebert/squeezebert-mnli-headless](https://huggingface.co/squeezebert/squeezebert-mnli-headless) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.3142 - Accuracy: 0.8824 - F1: 0.9137 ## 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: 32 - eval_batch_size: 32 - seed: 73 - 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 | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 115 | 0.4461 | 0.8162 | 0.8705 | | No log | 2.0 | 230 | 0.3844 | 0.8407 | 0.8866 | | No log | 3.0 | 345 | 0.3181 | 0.8848 | 0.9156 | | No log | 4.0 | 460 | 0.3159 | 0.8775 | 0.9091 | | 0.3723 | 5.0 | 575 | 0.3142 | 0.8824 | 0.9137 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3