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---
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: Whisper Base Indonesian
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: 26.607783604747446
---
<!-- 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. -->
# Whisper Base Indonesian
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: 0.4198
- Wer: 26.6078
## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.8238 | 4.01 | 500 | 0.6400 | 37.9750 |
| 0.6348 | 9.01 | 1000 | 0.5193 | 32.2477 |
| 0.4879 | 14.0 | 1500 | 0.4829 | 30.7250 |
| 0.4518 | 19.0 | 2000 | 0.4645 | 29.7037 |
| 0.4253 | 23.01 | 2500 | 0.4513 | 28.8757 |
| 0.4471 | 28.01 | 3000 | 0.4409 | 28.0937 |
| 0.3713 | 33.01 | 3500 | 0.4347 | 27.7854 |
| 0.3233 | 38.0 | 4000 | 0.4307 | 27.6382 |
| 0.3152 | 43.0 | 4500 | 0.4280 | 27.5324 |
| 0.3152 | 47.01 | 5000 | 0.4245 | 27.2196 |
| 0.333 | 52.01 | 5500 | 0.4227 | 26.9942 |
| 0.257 | 57.0 | 6000 | 0.4217 | 26.9620 |
| 0.25 | 62.0 | 6500 | 0.4214 | 26.8148 |
| 0.2587 | 66.01 | 7000 | 0.4206 | 26.7550 |
| 0.2765 | 71.01 | 7500 | 0.4198 | 26.6998 |
| 0.2664 | 76.01 | 8000 | 0.4198 | 26.6216 |
| 0.223 | 81.0 | 8500 | 0.4199 | 26.6446 |
| 0.2309 | 86.0 | 9000 | 0.4199 | 26.6538 |
| 0.233 | 90.01 | 9500 | 0.4198 | 26.6078 |
| 0.2647 | 95.01 | 10000 | 0.4198 | 26.6216 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
|