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-clinc
results: []
distilbert-base-uncased-finetuned-clinc
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: 0.7825
- Accuracy: 0.9152
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.3026 | 1.0 | 318 | 3.2852 | 0.7316 |
| 2.6284 | 2.0 | 636 | 1.8741 | 0.8510 |
| 1.5524 | 3.0 | 954 | 1.1640 | 0.8910 |
| 1.0182 | 4.0 | 1272 | 0.8668 | 0.9106 |
| 0.8045 | 5.0 | 1590 | 0.7825 | 0.9152 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0