---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: yt-special-batch4
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_9_0 id
      type: mozilla-foundation/common_voice_9_0
      config: id
      split: train
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 28.23428448830723
---

<!-- 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. -->

# yt-special-batch4

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_9_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6844
- Wer: 28.2343

## 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: 4
- eval_batch_size: 2
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 125.5137      | 0.79  | 1000 | 129.9009        | 149.0002 |
| 67.2464       | 1.59  | 2000 | 59.3172         | 298.8672 |
| 34.7799       | 2.38  | 3000 | 28.5244         | 134.9260 |
| 13.5007       | 3.17  | 4000 | 12.5162         | 51.1457  |
| 7.3781        | 3.97  | 5000 | 3.6844          | 28.2343  |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3