---
library_name: transformers
language:
- jv
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- javanese
- asr
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-Tiny-Java-v8
  results: []
---

<!-- 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-Tiny-Java-v8

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2450
- Wer: 0.1763

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.8116        | 1.6   | 1000  | 0.6226          | 0.4752 |
| 0.4683        | 3.2   | 2000  | 0.4166          | 0.4165 |
| 0.3047        | 4.8   | 3000  | 0.3430          | 0.3496 |
| 0.1679        | 6.4   | 4000  | 0.3180          | 0.2468 |
| 0.1405        | 8.0   | 5000  | 0.2874          | 0.2118 |
| 0.0856        | 9.6   | 6000  | 0.2819          | 0.2278 |
| 0.066         | 11.2  | 7000  | 0.2758          | 0.2034 |
| 0.0534        | 12.8  | 8000  | 0.2712          | 0.2234 |
| 0.044         | 14.4  | 9000  | 0.2690          | 0.2009 |
| 0.0393        | 16.0  | 10000 | 0.2669          | 0.1931 |
| 0.0344        | 17.6  | 11000 | 0.2601          | 0.1887 |
| 0.0292        | 19.2  | 12000 | 0.2627          | 0.1809 |
| 0.0272        | 20.8  | 13000 | 0.2597          | 0.1832 |
| 0.0231        | 22.4  | 14000 | 0.2556          | 0.1814 |
| 0.0223        | 24.0  | 15000 | 0.2562          | 0.1828 |
| 0.0192        | 25.6  | 16000 | 0.2534          | 0.1802 |
| 0.0167        | 27.2  | 17000 | 0.2512          | 0.1763 |
| 0.0178        | 28.8  | 18000 | 0.2496          | 0.1794 |
| 0.0143        | 30.4  | 19000 | 0.2461          | 0.1748 |
| 0.0147        | 32.0  | 20000 | 0.2450          | 0.1763 |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.7.0+cu128
- Datasets 2.16.0
- Tokenizers 0.21.1