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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: 0.9351612903225807
---
<!-- 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: 0.0562
- Accuracy: 0.9352
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5802 | 1.0 | 318 | 0.3269 | 0.6658 |
| 0.264 | 2.0 | 636 | 0.1590 | 0.8616 |
| 0.1571 | 3.0 | 954 | 0.1035 | 0.9113 |
| 0.1155 | 4.0 | 1272 | 0.0799 | 0.9223 |
| 0.0947 | 5.0 | 1590 | 0.0686 | 0.9268 |
| 0.0839 | 6.0 | 1908 | 0.0624 | 0.9310 |
| 0.0772 | 7.0 | 2226 | 0.0589 | 0.9323 |
| 0.0733 | 8.0 | 2544 | 0.0569 | 0.9355 |
| 0.0713 | 9.0 | 2862 | 0.0562 | 0.9352 |
### Framework versions
- Transformers 4.13.0
- Pytorch 1.12.0
- Datasets 1.16.1
- Tokenizers 0.10.3