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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: 0.947741935483871
---
<!-- 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: 0.3423
- Accuracy: 0.9477
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9781 | 1.0 | 318 | 2.1788 | 0.7426 |
| 1.6844 | 2.0 | 636 | 1.1132 | 0.8581 |
| 0.8838 | 3.0 | 954 | 0.6339 | 0.9145 |
| 0.5229 | 4.0 | 1272 | 0.4574 | 0.9332 |
| 0.3722 | 5.0 | 1590 | 0.3924 | 0.9432 |
| 0.3046 | 6.0 | 1908 | 0.3645 | 0.9458 |
| 0.2709 | 7.0 | 2226 | 0.3505 | 0.9465 |
| 0.2541 | 8.0 | 2544 | 0.3439 | 0.9468 |
| 0.2471 | 9.0 | 2862 | 0.3423 | 0.9477 |
### Framework versions
- Transformers 4.16.2
- Pytorch 2.0.1+cu118
- Datasets 1.16.1
- Tokenizers 0.13.3
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