metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results: []
distilbert-base-uncased-distilled-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: 0.3376
- Accuracy: 0.9490
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
3.1182 | 1.0 | 318 | 2.2772 | 0.7294 |
1.745 | 2.0 | 636 | 1.1424 | 0.8642 |
0.8968 | 3.0 | 954 | 0.6399 | 0.9148 |
0.519 | 4.0 | 1272 | 0.4578 | 0.9377 |
0.3634 | 5.0 | 1590 | 0.3908 | 0.9448 |
0.2938 | 6.0 | 1908 | 0.3648 | 0.9481 |
0.2599 | 7.0 | 2226 | 0.3542 | 0.9484 |
0.241 | 8.0 | 2544 | 0.3419 | 0.9477 |
0.2316 | 9.0 | 2862 | 0.3397 | 0.9477 |
0.2262 | 10.0 | 3180 | 0.3376 | 0.9490 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0