---
language:
- hu
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Base 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: 36.61815521981487
---

<!-- 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 CV18

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9673
- Wer Ortho: 43.0437
- Wer: 36.6182

## 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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.4737        | 0.1723 | 250  | 0.9877          | 61.4013   | 58.1242 |
| 0.3609        | 0.3446 | 500  | 0.9450          | 56.6701   | 52.1893 |
| 0.2894        | 0.5169 | 750  | 0.9007          | 53.2487   | 48.7805 |
| 0.2652        | 0.6892 | 1000 | 0.8833          | 52.5755   | 47.6039 |
| 0.225         | 0.8615 | 1250 | 0.8573          | 49.4478   | 45.3212 |
| 0.1414        | 1.0338 | 1500 | 0.8702          | 48.7835   | 43.8570 |
| 0.1361        | 1.2061 | 1750 | 0.8836          | 48.6700   | 43.0146 |
| 0.1297        | 1.3784 | 2000 | 0.8782          | 48.1922   | 42.8923 |
| 0.1285        | 1.5507 | 2250 | 0.8695          | 47.0576   | 41.8178 |
| 0.1241        | 1.7229 | 2500 | 0.8498          | 46.3403   | 40.9186 |
| 0.1198        | 1.8952 | 2750 | 0.8658          | 46.1928   | 40.0787 |
| 0.0552        | 2.0675 | 3000 | 0.8843          | 45.9684   | 39.5667 |
| 0.0608        | 2.2398 | 3250 | 0.8747          | 45.2347   | 39.5112 |
| 0.0576        | 2.4121 | 3500 | 0.8752          | 45.0557   | 39.7067 |
| 0.0629        | 2.5844 | 3750 | 0.8949          | 45.2297   | 39.2073 |
| 0.0613        | 2.7567 | 4000 | 0.9124          | 45.4137   | 39.0811 |
| 0.0542        | 2.9290 | 4250 | 0.8890          | 44.1443   | 38.4127 |
| 0.0248        | 3.1013 | 4500 | 0.9102          | 44.2388   | 37.9159 |
| 0.0253        | 3.2736 | 4750 | 0.9119          | 43.5908   | 37.3130 |
| 0.0248        | 3.4459 | 5000 | 0.9342          | 44.2325   | 37.8515 |
| 0.0238        | 3.6182 | 5250 | 0.9300          | 44.0018   | 37.6712 |
| 0.0241        | 3.7905 | 5500 | 0.9281          | 43.6614   | 37.3710 |
| 0.0231        | 3.9628 | 5750 | 0.9352          | 43.6715   | 37.7469 |
| 0.0101        | 4.1351 | 6000 | 0.9549          | 43.3387   | 37.2046 |
| 0.0083        | 4.3074 | 6250 | 0.9580          | 43.2795   | 36.9889 |
| 0.0082        | 4.4797 | 6500 | 0.9571          | 43.2152   | 37.0759 |
| 0.0087        | 4.6520 | 6750 | 0.9592          | 42.6290   | 36.3912 |
| 0.0077        | 4.8243 | 7000 | 0.9675          | 42.9139   | 36.5437 |
| 0.0076        | 4.9966 | 7250 | 0.9673          | 43.0437   | 36.6182 |


### Framework versions

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