--- language: - en license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: mobilebert_sa_GLUE_Experiment_data_aug_mrpc_256 results: - task: name: Text Classification type: text-classification dataset: name: GLUE MRPC type: glue args: mrpc metrics: - name: Accuracy type: accuracy value: 1.0 - name: F1 type: f1 value: 1.0 --- # mobilebert_sa_GLUE_Experiment_data_aug_mrpc_256 This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MRPC dataset. It achieves the following results on the evaluation set: - Loss: 0.0000 - Accuracy: 1.0 - F1: 1.0 - Combined Score: 1.0 ## 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: 128 - eval_batch_size: 128 - seed: 10 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| | 0.1854 | 1.0 | 1959 | 0.0199 | 0.9975 | 0.9982 | 0.9979 | | 0.04 | 2.0 | 3918 | 0.0050 | 0.9975 | 0.9982 | 0.9979 | | 0.0253 | 3.0 | 5877 | 0.0015 | 1.0 | 1.0 | 1.0 | | 0.0175 | 4.0 | 7836 | 0.0003 | 1.0 | 1.0 | 1.0 | | 0.0134 | 5.0 | 9795 | 0.0001 | 1.0 | 1.0 | 1.0 | | 0.0107 | 6.0 | 11754 | 0.0001 | 1.0 | 1.0 | 1.0 | | 0.0081 | 7.0 | 13713 | 0.0012 | 1.0 | 1.0 | 1.0 | | 0.0062 | 8.0 | 15672 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0061 | 9.0 | 17631 | 0.0001 | 1.0 | 1.0 | 1.0 | | 0.0044 | 10.0 | 19590 | 0.0002 | 1.0 | 1.0 | 1.0 | | 0.0041 | 11.0 | 21549 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0034 | 12.0 | 23508 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0029 | 13.0 | 25467 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0016 | 14.0 | 27426 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0019 | 15.0 | 29385 | 0.0140 | 0.9975 | 0.9982 | 0.9979 | | 0.0018 | 16.0 | 31344 | 0.0001 | 1.0 | 1.0 | 1.0 | | 0.0012 | 17.0 | 33303 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0013 | 18.0 | 35262 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0008 | 19.0 | 37221 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0011 | 20.0 | 39180 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0005 | 21.0 | 41139 | 0.0007 | 1.0 | 1.0 | 1.0 | | 0.0009 | 22.0 | 43098 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0004 | 23.0 | 45057 | 0.0000 | 1.0 | 1.0 | 1.0 | | 0.0004 | 24.0 | 47016 | 0.0000 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.26.0 - Pytorch 1.14.0a0+410ce96 - Datasets 2.9.0 - Tokenizers 0.13.2