--- language: - en license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: sa_BERT_48_mnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE MNLI type: glue config: mnli split: validation_matched args: mnli metrics: - name: Accuracy type: accuracy value: 0.7034174125305126 --- # sa_BERT_48_mnli This model is a fine-tuned version of [gokuls/bert_base_48](https://huggingface.co/gokuls/bert_base_48) on the GLUE MNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.7082 - Accuracy: 0.7034 ## 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: 4e-05 - train_batch_size: 96 - eval_batch_size: 96 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.9145 | 1.0 | 4091 | 0.8006 | 0.6536 | | 0.7442 | 2.0 | 8182 | 0.7245 | 0.6903 | | 0.6631 | 3.0 | 12273 | 0.7323 | 0.6979 | | 0.5942 | 4.0 | 16364 | 0.7073 | 0.7076 | | 0.5241 | 5.0 | 20455 | 0.7475 | 0.7016 | | 0.4526 | 6.0 | 24546 | 0.8377 | 0.7088 | | 0.3842 | 7.0 | 28637 | 0.8736 | 0.6956 | | 0.3213 | 8.0 | 32728 | 0.9334 | 0.6945 | | 0.2669 | 9.0 | 36819 | 1.0196 | 0.7027 | ### Framework versions - Transformers 4.30.2 - Pytorch 1.14.0a0+410ce96 - Datasets 2.13.0 - Tokenizers 0.13.3