---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      config: plus
      split: validation
      args: plus
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9509677419354838
---

<!-- 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-finetuned-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: 0.2354
- Accuracy: 0.9510

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0114        | 1.0   | 1907 | 0.9483          | 0.8577   |
| 0.2978        | 2.0   | 3814 | 0.2961          | 0.9368   |
| 0.097         | 3.0   | 5721 | 0.2422          | 0.9474   |
| 0.0393        | 4.0   | 7628 | 0.2349          | 0.9519   |
| 0.023         | 5.0   | 9535 | 0.2354          | 0.9510   |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.13.3