distilbert-base-uncased-finetuned-Global_Intent
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4771
- Accuracy: 0.8879
- F1: 0.8879
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- 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 | F1 |
|---|---|---|---|---|---|
| 1.6913 | 1.0 | 180 | 0.6445 | 0.8431 | 0.8367 |
| 0.4537 | 2.0 | 360 | 0.4791 | 0.8824 | 0.8798 |
| 0.2192 | 3.0 | 540 | 0.4941 | 0.8775 | 0.8753 |
| 0.1098 | 4.0 | 720 | 0.4912 | 0.8844 | 0.8826 |
| 0.0628 | 5.0 | 900 | 0.4771 | 0.8879 | 0.8879 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1