DIALOGUE_final_model
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0469
- Accuracy: 0.9902
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0037 | 0.31 | 15 | 0.0496 | 0.9902 |
| 0.0013 | 0.62 | 30 | 0.0437 | 0.9902 |
| 0.0008 | 0.94 | 45 | 0.0431 | 0.9902 |
| 0.0006 | 1.25 | 60 | 0.0387 | 0.9902 |
| 0.0005 | 1.56 | 75 | 0.0447 | 0.9902 |
| 0.0004 | 1.88 | 90 | 0.0465 | 0.9902 |
| 0.0004 | 2.19 | 105 | 0.0890 | 0.9804 |
| 0.0003 | 2.5 | 120 | 0.1008 | 0.9804 |
| 0.0004 | 2.81 | 135 | 0.0469 | 0.9902 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
google-bert/bert-base-uncased