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
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9448387096774193
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: 0.3163
- Accuracy: 0.9448
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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 2.3518 | 0.7510 |
| 2.7559 | 2.0 | 636 | 1.2235 | 0.8506 |
| 2.7559 | 3.0 | 954 | 0.6786 | 0.9168 |
| 1.0767 | 4.0 | 1272 | 0.4668 | 0.9368 |
| 0.4584 | 5.0 | 1590 | 0.3810 | 0.9410 |
| 0.4584 | 6.0 | 1908 | 0.3479 | 0.9435 |
| 0.2876 | 7.0 | 2226 | 0.3282 | 0.9455 |
| 0.2285 | 8.0 | 2544 | 0.3201 | 0.9452 |
| 0.2285 | 9.0 | 2862 | 0.3163 | 0.9448 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu102
- Datasets 2.0.0
- Tokenizers 0.12.1