---
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Hu CV18
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 18.0
      type: fleurs
      config: hu_hu
      split: None
      args: hu_hu
    metrics:
    - name: Wer
      type: wer
      value: 46.19517239639821
---

<!-- 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 Tiny Hu CV18

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2308
- Wer Ortho: 51.3968
- Wer: 46.1952

## 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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.5967        | 0.1723 | 250  | 1.2539          | 69.9246   | 66.9344 |
| 0.4456        | 0.3446 | 500  | 1.2200          | 65.5249   | 61.7108 |
| 0.3713        | 0.5169 | 750  | 1.1422          | 61.8665   | 58.0019 |
| 0.3337        | 0.6892 | 1000 | 1.1139          | 60.4332   | 55.7999 |
| 0.2829        | 0.8615 | 1250 | 1.1074          | 59.6528   | 56.2502 |
| 0.1931        | 1.0338 | 1500 | 1.1087          | 58.2686   | 53.8969 |
| 0.1855        | 1.2061 | 1750 | 1.1643          | 57.5828   | 52.8577 |
| 0.1827        | 1.3784 | 2000 | 1.1136          | 58.2951   | 54.2260 |
| 0.177         | 1.5507 | 2250 | 1.1326          | 57.4353   | 52.1628 |
| 0.1686        | 1.7229 | 2500 | 1.0970          | 54.8396   | 49.9067 |
| 0.1654        | 1.8952 | 2750 | 1.0957          | 56.3953   | 51.6975 |
| 0.0886        | 2.0675 | 3000 | 1.1150          | 53.5349   | 48.7805 |
| 0.0966        | 2.2398 | 3250 | 1.1417          | 54.4060   | 49.0113 |
| 0.0921        | 2.4121 | 3500 | 1.1387          | 53.9975   | 48.6001 |
| 0.0968        | 2.5844 | 3750 | 1.1587          | 53.8147   | 49.2660 |
| 0.0968        | 2.7567 | 4000 | 1.1459          | 52.8176   | 48.4438 |
| 0.086         | 2.9290 | 4250 | 1.1298          | 52.4784   | 47.4702 |
| 0.0456        | 3.1013 | 4500 | 1.1714          | 52.6663   | 47.3920 |
| 0.0487        | 3.2736 | 4750 | 1.1730          | 52.9524   | 48.1499 |
| 0.0475        | 3.4459 | 5000 | 1.1945          | 52.7898   | 47.3668 |
| 0.0442        | 3.6182 | 5250 | 1.2042          | 52.3410   | 47.3037 |
| 0.0434        | 3.7905 | 5500 | 1.1851          | 53.0205   | 47.7262 |
| 0.0438        | 3.9628 | 5750 | 1.1912          | 52.5869   | 48.0541 |
| 0.0211        | 4.1351 | 6000 | 1.2191          | 52.3562   | 47.9923 |
| 0.0198        | 4.3074 | 6250 | 1.2203          | 51.6136   | 46.6290 |
| 0.0185        | 4.4797 | 6500 | 1.2287          | 52.0297   | 46.4537 |
| 0.0196        | 4.6520 | 6750 | 1.2363          | 51.7183   | 46.2696 |
| 0.0196        | 4.8243 | 7000 | 1.2320          | 51.5594   | 46.0817 |
| 0.0178        | 4.9966 | 7250 | 1.2308          | 51.3968   | 46.1952 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1