---
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: model trenovan na en_de_en simi setu, nastaveni jazyka en overeni3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: odpovidajici nazvu modelu
      type: mozilla-foundation/common_voice_11_0
      args: 'config: ende, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 31.315296008572197
---

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# model trenovan na en_de_en simi setu, nastaveni jazyka en overeni3

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the odpovidajici nazvu modelu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2841
- Wer: 31.3153

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure




### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2