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: 0.944516129032258
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: 0.1831
- Accuracy: 0.9445
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 |
|---|---|---|---|---|
| 1.5638 | 1.0 | 318 | 1.0214 | 0.7245 |
| 0.7858 | 2.0 | 636 | 0.4895 | 0.8703 |
| 0.4104 | 3.0 | 954 | 0.2882 | 0.9181 |
| 0.2621 | 4.0 | 1272 | 0.2246 | 0.9323 |
| 0.2078 | 5.0 | 1590 | 0.2035 | 0.9377 |
| 0.1852 | 6.0 | 1908 | 0.1937 | 0.9406 |
| 0.1738 | 7.0 | 2226 | 0.1880 | 0.9419 |
| 0.1668 | 8.0 | 2544 | 0.1852 | 0.9442 |
| 0.163 | 9.0 | 2862 | 0.1833 | 0.9439 |
| 0.1608 | 10.0 | 3180 | 0.1831 | 0.9445 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.1+cu117
- Datasets 1.16.1
- Tokenizers 0.10.3