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: 0.947741935483871
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: 0.2570
- Accuracy: 0.9477
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 |
|---|---|---|---|---|
| 4.2156 | 1.0 | 318 | 3.1467 | 0.7535 |
| 2.3971 | 2.0 | 636 | 1.5584 | 0.8642 |
| 1.1564 | 3.0 | 954 | 0.7733 | 0.9103 |
| 0.5608 | 4.0 | 1272 | 0.4558 | 0.9335 |
| 0.3006 | 5.0 | 1590 | 0.3396 | 0.9419 |
| 0.1822 | 6.0 | 1908 | 0.2925 | 0.9426 |
| 0.1239 | 7.0 | 2226 | 0.2693 | 0.9448 |
| 0.0941 | 8.0 | 2544 | 0.2648 | 0.9465 |
| 0.0814 | 9.0 | 2862 | 0.2610 | 0.9461 |
| 0.0739 | 10.0 | 3180 | 0.2570 | 0.9477 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.0
- Datasets 1.16.1
- Tokenizers 0.10.3