metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinic-best
results: []
distilbert-base-uncased-finetuned-clinic-best
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: 0.1552
- Accuracy: 0.9410
Model description
“The parameters are as follows:
{'num_train_epoch': 9, 'alpha': 0.16484386886358915, 'temperature': 2}
These were obtained using grid search with Optuna.
Training and evaluation data
Clinic dataset from 'datasets'
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 0.8641 | 0.7094 |
| 1.1497 | 2.0 | 636 | 0.4002 | 0.8703 |
| 1.1497 | 3.0 | 954 | 0.2381 | 0.9113 |
| 0.3873 | 4.0 | 1272 | 0.1893 | 0.9313 |
| 0.2047 | 5.0 | 1590 | 0.1716 | 0.9339 |
| 0.2047 | 6.0 | 1908 | 0.1632 | 0.9387 |
| 0.165 | 7.0 | 2226 | 0.1589 | 0.9394 |
| 0.151 | 8.0 | 2544 | 0.1561 | 0.94 |
| 0.151 | 9.0 | 2862 | 0.1552 | 0.9410 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0