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-finetuned-clinc_v1
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      args: plus
    metrics:
    - type: accuracy
      value: 0.9480645161290323
      name: Accuracy
---

<!-- 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_v1

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: 0.2641
- Accuracy: 0.9481

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.779         | 1.0   | 318  | 2.8041          | 0.7542   |
| 2.1105        | 2.0   | 636  | 1.3468          | 0.8671   |
| 0.9905        | 3.0   | 954  | 0.6619          | 0.9206   |
| 0.4816        | 4.0   | 1272 | 0.4165          | 0.9368   |
| 0.2706        | 5.0   | 1590 | 0.3274          | 0.9468   |
| 0.1826        | 6.0   | 1908 | 0.2994          | 0.9458   |
| 0.1399        | 7.0   | 2226 | 0.2811          | 0.9487   |
| 0.1167        | 8.0   | 2544 | 0.2769          | 0.9477   |
| 0.1033        | 9.0   | 2862 | 0.2744          | 0.9474   |
| 0.0947        | 10.0  | 3180 | 0.2713          | 0.9484   |
| 0.0874        | 11.0  | 3498 | 0.2654          | 0.9513   |
| 0.0835        | 12.0  | 3816 | 0.2656          | 0.9487   |
| 0.08          | 13.0  | 4134 | 0.2668          | 0.9484   |
| 0.0781        | 14.0  | 4452 | 0.2650          | 0.9487   |
| 0.077         | 15.0  | 4770 | 0.2641          | 0.9481   |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.5.0+cu124
- Datasets 2.0.0
- Tokenizers 0.19.1
