metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
config: plus
split: validation
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9461290322580646
distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.2500
- Accuracy: 0.9461
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 |
|---|---|---|---|---|
| 4.247 | 1.0 | 318 | 3.1740 | 0.7555 |
| 2.4149 | 2.0 | 636 | 1.5652 | 0.8639 |
| 1.1633 | 3.0 | 954 | 0.7781 | 0.9061 |
| 0.5688 | 4.0 | 1272 | 0.4624 | 0.9342 |
| 0.3005 | 5.0 | 1590 | 0.3368 | 0.9429 |
| 0.1785 | 6.0 | 1908 | 0.2871 | 0.9429 |
| 0.1174 | 7.0 | 2226 | 0.2673 | 0.9458 |
| 0.0877 | 8.0 | 2544 | 0.2525 | 0.9465 |
| 0.0728 | 9.0 | 2862 | 0.2521 | 0.9465 |
| 0.0661 | 10.0 | 3180 | 0.2500 | 0.9461 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3