transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer cs dataset:mozilla-foundation/common_voice_11_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- cs
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper small + 2000 csen p5 concacat
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Prvni fine tuning spolecnych speakeru
      type: mozilla-foundation/common_voice_11_0
      args: 'config: csen, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 32.2286109123214
---

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# Whisper small + 2000 csen p5 concacat

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Prvni fine tuning spolecnych speakeru dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5955
- Wer: 32.2286

## 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: 100
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2369        | 1.09  | 200  | 0.5234          | 35.9820 |
| 0.0817        | 3.03  | 400  | 0.5461          | 35.6588 |
| 0.0192        | 4.12  | 600  | 0.5798          | 32.1176 |
| 0.011         | 6.06  | 800  | 0.5955          | 32.2286 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
