| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert-base-sst2 |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: glue |
| type: glue |
| config: sst2 |
| split: train |
| args: sst2 |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9036697247706422 |
| --- |
| |
| <!-- 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-sst2 |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3735 |
| - Accuracy: 0.9037 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 33 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.243 | 1.0 | 4210 | 0.3735 | 0.9037 | |
| | 0.1557 | 2.0 | 8420 | 0.3907 | 0.8922 | |
| | 0.1248 | 3.0 | 12630 | 0.3690 | 0.8945 | |
| | 0.1017 | 4.0 | 16840 | 0.5466 | 0.8830 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.22.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
|
|
