--- library_name: transformers language: - en license: apache-2.0 base_model: google/bert_uncased_L-4_H-128_A-2 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: bert_uncased_L-4_H-128_A-2_mnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE MNLI type: glue args: mnli metrics: - name: Accuracy type: accuracy value: 0.7331163547599675 --- # bert_uncased_L-4_H-128_A-2_mnli This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co./google/bert_uncased_L-4_H-128_A-2) on the GLUE MNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.6425 - Accuracy: 0.7331 ## 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: 256 - eval_batch_size: 256 - seed: 10 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.8752 | 1.0 | 1534 | 0.7743 | 0.6558 | | 0.7714 | 2.0 | 3068 | 0.7263 | 0.6857 | | 0.7255 | 3.0 | 4602 | 0.6946 | 0.7020 | | 0.6927 | 4.0 | 6136 | 0.6789 | 0.7087 | | 0.6662 | 5.0 | 7670 | 0.6657 | 0.7205 | | 0.6441 | 6.0 | 9204 | 0.6691 | 0.7229 | | 0.625 | 7.0 | 10738 | 0.6622 | 0.7258 | | 0.607 | 8.0 | 12272 | 0.6531 | 0.7314 | | 0.5894 | 9.0 | 13806 | 0.6613 | 0.7308 | | 0.5754 | 10.0 | 15340 | 0.6591 | 0.7293 | | 0.5615 | 11.0 | 16874 | 0.6635 | 0.7287 | | 0.5477 | 12.0 | 18408 | 0.6701 | 0.7344 | | 0.5343 | 13.0 | 19942 | 0.6699 | 0.7343 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.2.1+cu118 - Datasets 2.17.0 - Tokenizers 0.20.3