---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: breeze-listen-dsw-small-ml
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_16_0
      type: common_voice_16_0
      config: ml
      split: test
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 33.92029657089898
---

<!-- 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. -->

# breeze-listen-dsw-small-ml

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3826
- Wer: 33.9203

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4577        | 1.02  | 100  | 0.4824          | 58.3874 |
| 0.1781        | 2.04  | 200  | 0.3066          | 41.0658 |
| 0.0935        | 3.06  | 300  | 0.2903          | 35.6441 |
| 0.057         | 5.0   | 400  | 0.3289          | 36.6172 |
| 0.0285        | 6.03  | 500  | 0.3425          | 35.3197 |
| 0.0203        | 7.05  | 600  | 0.3647          | 34.3837 |
| 0.0103        | 8.07  | 700  | 0.3826          | 33.9203 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0