distilbert-base-uncased-UN-huongle
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: 0.0737
- Precision: 0.8363
- Recall: 0.8739
- F1: 0.8547
- Accuracy: 0.9852
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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 229 | 0.0517 | 0.8195 | 0.8567 | 0.8377 | 0.9834 |
| No log | 2.0 | 458 | 0.0529 | 0.7996 | 0.8600 | 0.8287 | 0.9823 |
| 0.063 | 3.0 | 687 | 0.0550 | 0.8331 | 0.8656 | 0.8490 | 0.9849 |
| 0.063 | 4.0 | 916 | 0.0698 | 0.8372 | 0.8725 | 0.8545 | 0.9852 |
| 0.0111 | 5.0 | 1145 | 0.0737 | 0.8363 | 0.8739 | 0.8547 | 0.9852 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.1
- Datasets 2.9.0
- Tokenizers 0.11.0
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