transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer id dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- id
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Indonesian - base
  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: 32.82730701996504
---

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# Breeze DSW Indonesian - base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5347
- Wer: 32.8273

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5452        | 1.02  | 200  | 0.5464          | 35.1688 |
| 0.3445        | 2.04  | 400  | 0.5405          | 34.0694 |
| 0.1397        | 3.07  | 600  | 0.5347          | 32.8273 |
| 0.0988        | 5.01  | 800  | 0.5654          | 35.6749 |
| 0.077         | 6.03  | 1000 | 0.5786          | 33.9452 |
| 0.0338        | 7.05  | 1200 | 0.6050          | 33.9820 |
| 0.0137        | 8.08  | 1400 | 0.6221          | 34.1016 |
| 0.0153        | 10.02 | 1600 | 0.6431          | 33.9038 |
| 0.0125        | 11.04 | 1800 | 0.6514          | 33.7520 |
| 0.0092        | 12.06 | 2000 | 0.6528          | 33.8256 |


### Framework versions

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