---
language:
- id
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Indonesian - tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 id
      type: mozilla-foundation/common_voice_16_0
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 43.44465912227436
---

<!-- 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 Indonesian - tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the mozilla-foundation/common_voice_16_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7090
- Wer: 43.4447

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.99          | 0.1   | 100  | 0.8486          | 54.2460 |
| 0.7896        | 1.04  | 200  | 0.7578          | 48.3899 |
| 0.4164        | 1.14  | 300  | 0.7388          | 49.3284 |
| 0.5456        | 2.09  | 400  | 0.7178          | 45.7954 |
| 0.4761        | 3.03  | 500  | 0.7109          | 45.2158 |
| 0.2674        | 3.13  | 600  | 0.7007          | 44.8431 |
| 0.3628        | 4.08  | 700  | 0.7026          | 44.2497 |
| 0.2565        | 5.02  | 800  | 0.7085          | 44.5073 |
| 0.2147        | 5.12  | 900  | 0.7090          | 43.4447 |
| 0.28          | 6.06  | 1000 | 0.7134          | 43.9553 |


### Framework versions

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