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: 0.9290322580645162
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: 0.0426
- Accuracy: 0.9290
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 |
|---|---|---|---|---|
| 0.83 | 1.0 | 318 | 0.4315 | 0.6626 |
| 0.328 | 2.0 | 636 | 0.1565 | 0.8494 |
| 0.1544 | 3.0 | 954 | 0.0834 | 0.9016 |
| 0.1005 | 4.0 | 1272 | 0.0607 | 0.9197 |
| 0.0794 | 5.0 | 1590 | 0.0518 | 0.9248 |
| 0.0693 | 6.0 | 1908 | 0.0470 | 0.9271 |
| 0.0635 | 7.0 | 2226 | 0.0447 | 0.9277 |
| 0.0602 | 8.0 | 2544 | 0.0430 | 0.9306 |
| 0.0584 | 9.0 | 2862 | 0.0426 | 0.9290 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.12.1
- Datasets 1.16.1
- Tokenizers 0.10.3