--- tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: squeezebert-uncased-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: 0.8137254901960784 - name: F1 type: f1 value: 0.8733333333333333 --- # squeezebert-uncased-finetuned-mrpc This model is a fine-tuned version of [squeezebert/squeezebert-uncased](https://huggingface.co/squeezebert/squeezebert-uncased) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.4261 - Accuracy: 0.8137 - F1: 0.8733 ## 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: 24 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 115 | 0.5015 | 0.7843 | 0.8603 | | No log | 2.0 | 230 | 0.4571 | 0.7941 | 0.8627 | | No log | 3.0 | 345 | 0.4261 | 0.8137 | 0.8733 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3