---
language:
- de
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Tiny CV de
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0 de 5%
      type: mozilla-foundation/common_voice_16_0
      config: de
      split: None
      args: 'config: de, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 72.91819291819291
---

<!-- 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 CV de

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 de 5% dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7117
- Wer: 72.9182

## 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: 1.35e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6076        | 0.2252 | 250  | 0.8347          | 76.3126 |
| 0.5955        | 0.4505 | 500  | 0.7893          | 79.1697 |
| 0.5179        | 0.6757 | 750  | 0.7593          | 82.1978 |
| 0.5189        | 0.9009 | 1000 | 0.7370          | 73.0159 |
| 0.3644        | 1.1261 | 1250 | 0.7254          | 84.1270 |
| 0.394         | 1.3514 | 1500 | 0.7183          | 73.4066 |
| 0.3672        | 1.5766 | 1750 | 0.7152          | 73.1136 |
| 0.3751        | 1.8018 | 2000 | 0.7117          | 72.9182 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1