---
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-batch12-lr4-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: 17.593742811134117
---

<!-- 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-batch12-lr4-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: 0.4567
- Wer: 17.5937

## 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: 0.0001
- train_batch_size: 12
- eval_batch_size: 6
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3743        | 1.45  | 1000 | 0.5498          | 28.2724 |
| 0.1633        | 2.9   | 2000 | 0.5010          | 25.1530 |
| 0.0505        | 4.35  | 3000 | 0.5049          | 22.1670 |
| 0.0136        | 5.81  | 4000 | 0.4631          | 18.6335 |
| 0.0005        | 7.26  | 5000 | 0.4567          | 17.5937 |


### Framework versions

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