---
language:
- de
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0,facebook/voxpopuli,google/fleurs
metrics:
- wer
model-index:
- name: Whisper LargeV2 German
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0,facebook/voxpopuli,google/fleurs
        de,de,de_de
      type: mozilla-foundation/common_voice_11_0,facebook/voxpopuli,google/fleurs
      config: de
      split: test
      args: de
    metrics:
    - name: Wer
      type: wer
      value: 6.313937972585015
---

<!-- 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 LargeV2 German

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0,facebook/voxpopuli,google/fleurs de,de,de_de dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1307
- Wer: 6.3139

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.127         | 0.17  | 500  | 0.1569          | 7.2588 |
| 0.1116        | 0.33  | 1000 | 0.1505          | 7.2372 |
| 0.1132        | 0.5   | 1500 | 0.1435          | 6.8821 |
| 0.0939        | 0.67  | 2000 | 0.1354          | 6.5343 |
| 0.0819        | 0.83  | 2500 | 0.1339          | 6.4979 |
| 0.0892        | 1.0   | 3000 | 0.1307          | 6.3139 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2

### Author: @daveni