---
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
---

<!-- 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 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

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6.600000000000001e-06
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4886        | 0.1   | 100  | 0.3900          | 12.3225 |
| 0.2534        | 0.2   | 200  | 0.2826          | 15.7514 |
| 0.1143        | 1.05  | 300  | 0.2457          | 16.4211 |
| 0.1134        | 1.15  | 400  | 0.2496          | 14.2245 |
| 0.1186        | 1.25  | 500  | 0.2511          | 13.5280 |
| 0.054         | 2.1   | 600  | 0.2694          | 15.6175 |
| 0.0449        | 2.2   | 700  | 0.2743          | 21.0019 |
| 0.0224        | 3.05  | 800  | 0.2812          | 24.1897 |
| 0.0241        | 3.15  | 900  | 0.2828          | 31.6368 |
| 0.0324        | 3.25  | 1000 | 0.2841          | 31.3153 |


### Framework versions

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