---
language:
- hu
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Hu CV17
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: common_voice_11_0
      config: hu
      split: None
      args: hu
    metrics:
    - name: Wer
      type: wer
      value: 8.132226504595316
---

<!-- 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 Base Hu CV17

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1148
- Wer Ortho: 8.9576
- Wer: 8.1322

## 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: 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
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.5156        | 0.3298 | 250  | 0.5620          | 52.2010   | 49.0898 |
| 0.3906        | 0.6596 | 500  | 0.4262          | 43.7131   | 40.2668 |
| 0.3276        | 0.9894 | 750  | 0.3243          | 33.3915   | 30.2728 |
| 0.2161        | 1.3193 | 1000 | 0.2639          | 27.8152   | 24.9778 |
| 0.2009        | 1.6491 | 1250 | 0.2314          | 24.8705   | 21.9923 |
| 0.1835        | 1.9789 | 1500 | 0.1938          | 21.4922   | 18.8260 |
| 0.0973        | 2.3087 | 1750 | 0.1748          | 18.8396   | 16.0243 |
| 0.0963        | 2.6385 | 2000 | 0.1600          | 17.0240   | 14.8651 |
| 0.0913        | 2.9683 | 2250 | 0.1414          | 14.0853   | 12.1198 |
| 0.046         | 3.2982 | 2500 | 0.1374          | 13.2000   | 11.4468 |
| 0.0447        | 3.6280 | 2750 | 0.1306          | 12.5677   | 10.9191 |
| 0.0409        | 3.9578 | 3000 | 0.1216          | 11.1436   | 9.8251  |
| 0.0173        | 4.2876 | 3250 | 0.1205          | 10.4812   | 9.2292  |
| 0.0165        | 4.6174 | 3500 | 0.1180          | 10.2343   | 9.0898  |
| 0.0152        | 4.9472 | 3750 | 0.1149          | 9.6200    | 8.5562  |
| 0.0061        | 5.2770 | 4000 | 0.1149          | 9.1021    | 8.1589  |
| 0.0056        | 5.6069 | 4250 | 0.1144          | 9.2406    | 8.2864  |
| 0.006         | 5.9367 | 4500 | 0.1138          | 9.0630    | 8.1559  |
| 0.0036        | 6.2665 | 4750 | 0.1148          | 9.0148    | 8.1737  |
| 0.0033        | 6.5963 | 5000 | 0.1148          | 8.9576    | 8.1322  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1