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: 0.2617
- 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 |
|---|---|---|---|---|
| 2.5019 | 1.0 | 318 | 1.8299 | 0.7542 |
| 1.4175 | 2.0 | 636 | 0.9465 | 0.8694 |
| 0.7545 | 3.0 | 954 | 0.5415 | 0.9194 |
| 0.448 | 4.0 | 1272 | 0.3804 | 0.9374 |
| 0.3093 | 5.0 | 1590 | 0.3157 | 0.9448 |
| 0.2466 | 6.0 | 1908 | 0.2878 | 0.9474 |
| 0.2147 | 7.0 | 2226 | 0.2727 | 0.9490 |
| 0.1976 | 8.0 | 2544 | 0.2666 | 0.9484 |
| 0.1885 | 9.0 | 2862 | 0.2637 | 0.9490 |
| 0.1851 | 10.0 | 3180 | 0.2617 | 0.9494 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.1+cu116
- Datasets 1.16.1
- Tokenizers 0.10.3