---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_9_0
metrics:
- wer
model-index:
- name: cv9-special-batch8-lr3-small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_9_0
      type: common_voice_9_0
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 104.82631700023003
---

<!-- 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. -->

# cv9-special-batch8-lr3-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_9_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7744
- Wer: 104.8263

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 4
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9757        | 0.97  | 1000 | 3.3365          | 126.4090 |
| 3.4153        | 1.94  | 2000 | 2.9701          | 105.5855 |
| 2.9747        | 2.9   | 3000 | 2.8029          | 99.2086  |
| 2.6552        | 3.87  | 4000 | 2.6929          | 102.4891 |
| 1.9795        | 4.84  | 5000 | 2.7744          | 104.8263 |


### Framework versions

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