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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: 0.9387096774193548
---
<!-- 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: 0.0878
- Accuracy: 0.9387
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0369 | 1.0 | 318 | 0.5902 | 0.6987 |
| 0.4468 | 2.0 | 636 | 0.2434 | 0.8606 |
| 0.2204 | 3.0 | 954 | 0.1412 | 0.9113 |
| 0.1478 | 4.0 | 1272 | 0.1121 | 0.9252 |
| 0.1206 | 5.0 | 1590 | 0.1010 | 0.93 |
| 0.1086 | 6.0 | 1908 | 0.0947 | 0.9345 |
| 0.1009 | 7.0 | 2226 | 0.0916 | 0.9368 |
| 0.0966 | 8.0 | 2544 | 0.0896 | 0.9381 |
| 0.0939 | 9.0 | 2862 | 0.0881 | 0.9390 |
| 0.0928 | 10.0 | 3180 | 0.0878 | 0.9387 |
### Framework versions
- Transformers 4.11.3
- Pytorch 2.0.0+cu118
- Datasets 1.16.1
- Tokenizers 0.10.3
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