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my_SA_distilbert_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4408
- Accuracy: 0.9166
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4079 | 1.0 | 1124 | 0.3399 | 0.8832 |
0.2688 | 2.0 | 2248 | 0.3037 | 0.9037 |
0.1868 | 3.0 | 3372 | 0.2777 | 0.9135 |
0.1476 | 4.0 | 4496 | 0.2797 | 0.9186 |
0.1188 | 5.0 | 5620 | 0.3400 | 0.9157 |
0.0934 | 6.0 | 6744 | 0.3471 | 0.9148 |
0.0779 | 7.0 | 7868 | 0.3694 | 0.9201 |
0.0584 | 8.0 | 8992 | 0.4350 | 0.9081 |
0.0499 | 9.0 | 10116 | 0.4336 | 0.9146 |
0.0405 | 10.0 | 11240 | 0.4408 | 0.9166 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3