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: 0.9493548387096774
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: 0.2316
- 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 |
---|---|---|---|---|
2.1042 | 1.0 | 318 | 1.5124 | 0.7487 |
1.1742 | 2.0 | 636 | 0.7825 | 0.8735 |
0.6319 | 3.0 | 954 | 0.4544 | 0.9203 |
0.3826 | 4.0 | 1272 | 0.3230 | 0.9345 |
0.2712 | 5.0 | 1590 | 0.2731 | 0.9448 |
0.2233 | 6.0 | 1908 | 0.2517 | 0.9484 |
0.1992 | 7.0 | 2226 | 0.2402 | 0.95 |
0.1863 | 8.0 | 2544 | 0.2354 | 0.9490 |
0.1792 | 9.0 | 2862 | 0.2331 | 0.9497 |
0.1766 | 10.0 | 3180 | 0.2316 | 0.9494 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3