---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: breeze-dsw-tiny-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: 55.097312326227986
---

<!-- 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-dsw-tiny-ml

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7383
- Wer: 55.0973

## 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: 32
- eval_batch_size: 16
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.1736        | 2.02  | 100  | 1.1670          | 99.7776 |
| 0.9647        | 4.04  | 200  | 1.0049          | 95.4866 |
| 0.5311        | 7.02  | 300  | 0.6807          | 74.5598 |
| 0.3036        | 9.04  | 400  | 0.5410          | 61.5755 |
| 0.1672        | 12.02 | 500  | 0.5146          | 56.5709 |
| 0.1006        | 14.04 | 600  | 0.5503          | 54.3744 |
| 0.0484        | 17.02 | 700  | 0.5859          | 54.5042 |
| 0.0305        | 19.04 | 800  | 0.6562          | 55.4124 |
| 0.0147        | 22.02 | 900  | 0.7095          | 54.8749 |
| 0.0116        | 24.04 | 1000 | 0.7383          | 55.0973 |


### Framework versions

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