---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
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
      config: plus
      split: validation
      args: plus
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9419354838709677
---

<!-- 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: 0.3313
- Accuracy: 0.9419

## 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: 0.00016475242401724032
- 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: cosine
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 318  | 0.3697          | 0.9132   |
| 1.0928        | 2.0   | 636  | 0.3539          | 0.9226   |
| 1.0928        | 3.0   | 954  | 0.3790          | 0.9281   |
| 0.1164        | 4.0   | 1272 | 0.3579          | 0.9345   |
| 0.0587        | 5.0   | 1590 | 0.3705          | 0.9281   |
| 0.0587        | 6.0   | 1908 | 0.3543          | 0.9410   |
| 0.0344        | 7.0   | 2226 | 0.3665          | 0.9348   |
| 0.0244        | 8.0   | 2544 | 0.3510          | 0.9358   |
| 0.0244        | 9.0   | 2862 | 0.3344          | 0.9423   |
| 0.0153        | 10.0  | 3180 | 0.3335          | 0.9403   |
| 0.0153        | 11.0  | 3498 | 0.3302          | 0.9426   |
| 0.0126        | 12.0  | 3816 | 0.3305          | 0.9423   |
| 0.0103        | 13.0  | 4134 | 0.3301          | 0.9423   |
| 0.0103        | 14.0  | 4452 | 0.3311          | 0.9416   |
| 0.0095        | 15.0  | 4770 | 0.3313          | 0.9419   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.4.0
- Tokenizers 0.19.1