---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-ai-nose
  results: []
---

<!-- 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. -->

# whisper-ai-nose

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 14.3032

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.8578        | 0.8163  | 100  | 0.0827          | 9.4132   |
| 0.2317        | 1.6327  | 200  | 0.0545          | 18.9487  |
| 0.079         | 2.4490  | 300  | 0.0488          | 204.5232 |
| 0.0586        | 3.2653  | 400  | 0.0493          | 227.9951 |
| 0.0396        | 4.0816  | 500  | 0.0277          | 23.9609  |
| 0.1368        | 4.8980  | 600  | 0.2826          | 94.6210  |
| 0.1721        | 5.7143  | 700  | 0.0024          | 145.1100 |
| 0.0246        | 6.5306  | 800  | 0.0024          | 22.9829  |
| 0.0143        | 7.3469  | 900  | 0.0008          | 25.1834  |
| 0.0185        | 8.1633  | 1000 | 0.0026          | 69.4377  |
| 0.0171        | 8.9796  | 1100 | 0.0069          | 22.4939  |
| 0.0229        | 9.7959  | 1200 | 0.0004          | 43.6430  |
| 0.0033        | 10.6122 | 1300 | 0.0018          | 16.8704  |
| 0.0073        | 11.4286 | 1400 | 0.0076          | 14.6699  |
| 0.0053        | 12.2449 | 1500 | 0.0030          | 14.4254  |
| 0.0038        | 13.0612 | 1600 | 0.0027          | 13.0807  |
| 0.0004        | 13.8776 | 1700 | 0.0000          | 13.4474  |
| 0.0008        | 14.6939 | 1800 | 0.0001          | 11.4914  |
| 0.0014        | 15.5102 | 1900 | 0.0002          | 11.9804  |
| 0.0047        | 16.3265 | 2000 | 0.0002          | 14.9144  |
| 0.0031        | 17.1429 | 2100 | 0.0001          | 15.1589  |
| 0.0018        | 17.9592 | 2200 | 0.0002          | 15.7702  |
| 0.0019        | 18.7755 | 2300 | 0.0000          | 15.1589  |
| 0.0006        | 19.5918 | 2400 | 0.0000          | 15.0367  |
| 0.0001        | 20.4082 | 2500 | 0.0000          | 14.0587  |
| 0.0001        | 21.2245 | 2600 | 0.0000          | 14.4254  |
| 0.0           | 22.0408 | 2700 | 0.0000          | 14.1809  |
| 0.0           | 22.8571 | 2800 | 0.0000          | 14.5477  |
| 0.0           | 23.6735 | 2900 | 0.0000          | 14.4254  |
| 0.0           | 24.4898 | 3000 | 0.0000          | 14.4254  |
| 0.0           | 25.3061 | 3100 | 0.0000          | 14.4254  |
| 0.0           | 26.1224 | 3200 | 0.0000          | 14.3032  |
| 0.0           | 26.9388 | 3300 | 0.0000          | 14.3032  |
| 0.0           | 27.7551 | 3400 | 0.0000          | 14.4254  |
| 0.0           | 28.5714 | 3500 | 0.0000          | 14.3032  |
| 0.0           | 29.3878 | 3600 | 0.0000          | 14.3032  |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1