---
language:
- sk
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Slovak test on Czech
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: sk
      split: test
      args: sk
    metrics:
    - name: Wer
      type: wer
      value: 35.43550690147549
---

<!-- 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 Small Slovak test on Czech

This model is a fine-tuned version of [mikr/whisper-small-cs-cv11](https://huggingface.co/mikr/whisper-small-cs-cv11) on the mozilla-foundation/common_voice_11_0 sk dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7223
- Wer: 35.4355

## 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: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.001         | 21.0  | 1000 | 0.6507          | 37.3275 |
| 0.0003        | 42.01 | 2000 | 0.6954          | 36.1138 |
| 0.0002        | 63.01 | 3000 | 0.7223          | 35.4355 |
| 0.0001        | 85.0  | 4000 | 0.7388          | 35.5902 |
| 0.0001        | 106.0 | 5000 | 0.7465          | 35.6735 |


### Framework versions

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