---
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 not simlar setu, nastaveni jazyka en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: xbilek25/train_set_1st_1000_de_en_de
      type: mozilla-foundation/common_voice_11_0
      args: 'config: ende, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 14.517374517374519
---

<!-- 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. -->

# model trenovan na en-de-en not simlar setu, nastaveni jazyka en

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the xbilek25/train_set_1st_1000_de_en_de dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3121
- Wer: 14.5174

## 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: 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: 1
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2582        | 0.1   | 200  | 0.2807          | 15.3153 |
| 0.0882        | 1.07  | 400  | 0.2688          | 14.0541 |
| 0.0293        | 2.05  | 600  | 0.2696          | 13.5907 |
| 0.0152        | 3.02  | 800  | 0.2752          | 13.8739 |
| 0.0106        | 3.12  | 1000 | 0.2862          | 13.9511 |
| 0.0046        | 4.1   | 1200 | 0.2895          | 13.5907 |
| 0.0023        | 5.08  | 1400 | 0.3044          | 14.3372 |
| 0.0023        | 6.05  | 1600 | 0.3060          | 14.1828 |
| 0.0016        | 7.03  | 1800 | 0.3100          | 14.3887 |
| 0.0015        | 7.12  | 2000 | 0.3121          | 14.5174 |


### Framework versions

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