---
language:
- de
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- rmacek/ORF-whisper-small
metrics:
- wer
model-index:
- name: Whisper ORF Bundeslaender
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ZIB2 Common Voice
      type: rmacek/ORF-whisper-small
      args: 'config: de, split: test'
    metrics:
    - type: wer
      value: 29.46806728721495
      name: Wer
---

<!-- 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 ORF Bundeslaender

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ZIB2 Common Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7149
- Wer: 29.4681

## 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: 0.0001
- 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: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.5717        | 1.7153  | 1000 | 0.6098          | 35.2851 |
| 0.41          | 3.4305  | 2000 | 0.6053          | 32.7056 |
| 0.386         | 5.1458  | 3000 | 0.6148          | 26.9699 |
| 0.3123        | 6.8611  | 4000 | 0.6345          | 26.4842 |
| 0.2183        | 8.5763  | 5000 | 0.6622          | 28.1329 |
| 0.2231        | 10.2916 | 6000 | 0.6901          | 28.5253 |
| 0.2259        | 12.0069 | 7000 | 0.7028          | 27.4413 |
| 0.1708        | 13.7221 | 8000 | 0.7149          | 29.4681 |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1