<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased-cls-intent
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: 0.0041
- Accuracy: 1.0
- F1: 1.0
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: 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.4784 | 1.0 | 39 | 0.3607 | 0.8846 | 0.8855 |
0.1721 | 2.0 | 78 | 0.0180 | 1.0 | 1.0 |
0.0697 | 3.0 | 117 | 0.0066 | 1.0 | 1.0 |
0.039 | 4.0 | 156 | 0.0047 | 1.0 | 1.0 |
0.0283 | 5.0 | 195 | 0.0041 | 1.0 | 1.0 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3