| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - nyu-mll/glue | |
| metrics: | |
| - f1 | |
| - accuracy | |
| base_model: bert-base-cased | |
| model-index: | |
| - name: glue_sst_classifier | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: glue | |
| type: glue | |
| args: sst2 | |
| metrics: | |
| - type: f1 | |
| value: 0.9033707865168539 | |
| name: F1 | |
| - type: accuracy | |
| value: 0.9013761467889908 | |
| 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. --> | |
| # glue_sst_classifier | |
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2359 | |
| - F1: 0.9034 | |
| - Accuracy: 0.9014 | |
| ## 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: 1e-05 | |
| - train_batch_size: 128 | |
| - eval_batch_size: 128 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 1.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| | |
| | 0.3653 | 0.19 | 100 | 0.3213 | 0.8717 | 0.8727 | | |
| | 0.291 | 0.38 | 200 | 0.2662 | 0.8936 | 0.8911 | | |
| | 0.2239 | 0.57 | 300 | 0.2417 | 0.9081 | 0.9060 | | |
| | 0.2306 | 0.76 | 400 | 0.2359 | 0.9105 | 0.9094 | | |
| | 0.2185 | 0.95 | 500 | 0.2371 | 0.9011 | 0.8991 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |