pytorch distilbert generated_from_trainer dataset:clinc_oos license:apache-2.0 model-index region:us
---
datasets:
- clinc_oos
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-distilled-clinc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      args: plus
    metrics:
    - type: accuracy
      value: 0.95
      name: Accuracy
---

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# 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: 0.3139
- Accuracy: 0.95

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1701        | 1.0   | 318  | 2.3152          | 0.7539   |
| 1.7492        | 2.0   | 636  | 1.1181          | 0.8677   |
| 0.8498        | 3.0   | 954  | 0.5945          | 0.9229   |
| 0.4676        | 4.0   | 1272 | 0.4263          | 0.9381   |
| 0.321         | 5.0   | 1590 | 0.3711          | 0.9468   |
| 0.2625        | 6.0   | 1908 | 0.3501          | 0.9474   |
| 0.2322        | 7.0   | 2226 | 0.3340          | 0.9510   |
| 0.2151        | 8.0   | 2544 | 0.3280          | 0.9494   |
| 0.2049        | 9.0   | 2862 | 0.3253          | 0.9484   |
| 0.1989        | 10.0  | 3180 | 0.3221          | 0.9494   |
| 0.1934        | 11.0  | 3498 | 0.3162          | 0.9519   |
| 0.1905        | 12.0  | 3816 | 0.3147          | 0.9503   |
| 0.1881        | 13.0  | 4134 | 0.3154          | 0.9487   |
| 0.1865        | 14.0  | 4452 | 0.3143          | 0.9506   |
| 0.186         | 15.0  | 4770 | 0.3139          | 0.95     |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.4.1+cu121
- Datasets 1.16.1
- Tokenizers 0.19.1
