bert-base-uncased-finetuned-sst2
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3900
- Accuracy: 0.9312
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1797 | 1.0 | 4210 | 0.2223 | 0.9232 |
| 0.1299 | 2.0 | 8420 | 0.3560 | 0.9094 |
| 0.0842 | 3.0 | 12630 | 0.3163 | 0.9232 |
| 0.0537 | 4.0 | 16840 | 0.3400 | 0.9243 |
| 0.0368 | 5.0 | 21050 | 0.3900 | 0.9312 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Tech-oriented/bert-base-uncased-finetuned-sst2
Base model
google-bert/bert-base-uncased