---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- simodo79/Vaudeville
metrics:
- wer
model-index:
- name: Whisper Small Vdv
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Vaudeville
      type: simodo79/Vaudeville
      config: default
      split: None
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0
pipeline_tag: automatic-speech-recognition
library_name: transformers
---

<!-- 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 Vdv

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0

## 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 0.0           | 500.0  | 1000 | 0.0000          | 0.0 |
| 0.0           | 1000.0 | 2000 | 0.0000          | 0.0 |
| 0.0           | 1500.0 | 3000 | 0.0000          | 0.0 |
| 0.0           | 2000.0 | 4000 | 0.0000          | 0.0 |
| 0.0           | 2500.0 | 5000 | 0.0000          | 0.0 |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.12.0
- Datasets 2.20.0
- Tokenizers 0.19.1