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: 0.9493548387096774
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: 0.3171
- Accuracy: 0.9494
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 |
|---|---|---|---|---|
| 3.9637 | 1.0 | 318 | 2.9527 | 0.7529 |
| 2.2541 | 2.0 | 636 | 1.4652 | 0.8632 |
| 1.1032 | 3.0 | 954 | 0.7510 | 0.9097 |
| 0.5665 | 4.0 | 1272 | 0.4749 | 0.9342 |
| 0.3331 | 5.0 | 1590 | 0.3736 | 0.9426 |
| 0.2338 | 6.0 | 1908 | 0.3400 | 0.9458 |
| 0.1874 | 7.0 | 2226 | 0.3289 | 0.9481 |
| 0.1658 | 8.0 | 2544 | 0.3179 | 0.9474 |
| 0.1553 | 9.0 | 2862 | 0.3183 | 0.9490 |
| 0.1503 | 10.0 | 3180 | 0.3171 | 0.9494 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0