DIALOGUE_two
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3804
- Precision: 0.9762
- Recall: 0.9737
- F1: 0.9736
- Accuracy: 0.9737
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: 1e-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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
1.3711 | 0.31 | 15 | 1.3213 | 0.5848 | 0.5132 | 0.4588 | 0.5132 |
1.2829 | 0.62 | 30 | 1.1830 | 0.7679 | 0.7237 | 0.7027 | 0.7237 |
1.1039 | 0.94 | 45 | 0.9695 | 0.8939 | 0.8158 | 0.8094 | 0.8158 |
0.9122 | 1.25 | 60 | 0.7720 | 0.9499 | 0.9474 | 0.9473 | 0.9474 |
0.7581 | 1.56 | 75 | 0.6220 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
0.6483 | 1.88 | 90 | 0.5096 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
0.5277 | 2.19 | 105 | 0.4330 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
0.4708 | 2.5 | 120 | 0.4003 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
0.4622 | 2.81 | 135 | 0.3804 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for SharonTudi/DIALOGUE_two
Base model
distilbert/distilbert-base-cased