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This model is a fine-tuned version of bert-large-uncased on the SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3109
- Accuracy: 0.9255
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: not_parallel
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 2105 | 0.2167 | 0.9232 |
| 0.2049 | 2.0 | 4210 | 0.2375 | 0.9278 |
| 0.123 | 3.0 | 6315 | 0.2636 | 0.9243 |
| 0.0839 | 4.0 | 8420 | 0.2865 | 0.9243 |
| 0.058 | 5.0 | 10525 | 0.3109 | 0.9255 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu113
- Datasets 2.7.1
- Tokenizers 0.11.6
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Dataset used to train TehranNLP-org/bert-large-sst2
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Evaluation results
- Accuracy on SST2self-reported0.925