| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - accuracy | |
| base_model: bert-base-uncased | |
| model-index: | |
| - name: bert-base-uncased-qnli | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: GLUE QNLI | |
| type: glue | |
| args: qnli | |
| metrics: | |
| - type: accuracy | |
| value: 0.9125022881200805 | |
| name: Accuracy | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # bert-base-uncased-qnli | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QNLI dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3208 | |
| - Accuracy: 0.9125 | |
| ## 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: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.289 | 1.0 | 3274 | 0.2289 | 0.9094 | | |
| | 0.1801 | 2.0 | 6548 | 0.2493 | 0.9118 | | |
| | 0.1074 | 3.0 | 9822 | 0.3208 | 0.9125 | | |
| ### Framework versions | |
| - Transformers 4.20.0.dev0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |