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---
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: 0.9487096774193549
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3445
- Accuracy: 0.9487
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.4915 | 1.0 | 318 | 2.5863 | 0.7506 |
| 1.985 | 2.0 | 636 | 1.3027 | 0.8655 |
| 0.9995 | 3.0 | 954 | 0.6997 | 0.9116 |
| 0.5484 | 4.0 | 1272 | 0.4723 | 0.9374 |
| 0.364 | 5.0 | 1590 | 0.3997 | 0.9435 |
| 0.2855 | 6.0 | 1908 | 0.3724 | 0.9439 |
| 0.2475 | 7.0 | 2226 | 0.3573 | 0.9481 |
| 0.2267 | 8.0 | 2544 | 0.3517 | 0.9458 |
| 0.2173 | 9.0 | 2862 | 0.3480 | 0.9468 |
| 0.2112 | 10.0 | 3180 | 0.3445 | 0.9487 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.12.0
- Datasets 1.16.1
- Tokenizers 0.10.3
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