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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: 0.3060
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.643 | 1.0 | 318 | 1.9110 | 0.7452 |
| 1.4751 | 2.0 | 636 | 0.9678 | 0.8606 |
| 0.7736 | 3.0 | 954 | 0.5578 | 0.9168 |
| 0.4652 | 4.0 | 1272 | 0.4081 | 0.9352 |
| 0.3364 | 5.0 | 1590 | 0.3538 | 0.9442 |
| 0.2801 | 6.0 | 1908 | 0.3294 | 0.9465 |
| 0.2515 | 7.0 | 2226 | 0.3165 | 0.9471 |
| 0.2366 | 8.0 | 2544 | 0.3107 | 0.9487 |
| 0.2292 | 9.0 | 2862 | 0.3069 | 0.9490 |
| 0.2247 | 10.0 | 3180 | 0.3060 | 0.9487 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.12.1.post200
- Datasets 1.16.1
- Tokenizers 0.10.3
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