bert-base-uncased-finetuned-sst2
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3186
- Accuracy: 0.9278
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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 132 | 0.3186 | 0.9278 |
| No log | 2.0 | 264 | 0.3655 | 0.9243 |
| No log | 3.0 | 396 | 0.3763 | 0.9255 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for minseok0809/bert-base-uncased-finetuned-sst2
Base model
google-bert/bert-base-uncasedDataset used to train minseok0809/bert-base-uncased-finetuned-sst2
Space using minseok0809/bert-base-uncased-finetuned-sst2 1
Evaluation results
- Accuracy on gluevalidation set self-reported0.928