---
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-Large-v2-Java-v2
  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-Large-v2-Java-v2

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: 0.1112
- Wer: 0.0612

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4821        | 0.4   | 1000  | 0.3570          | 0.2268 |
| 0.4761        | 0.8   | 2000  | 0.3474          | 0.2397 |
| 0.3099        | 1.2   | 3000  | 0.3075          | 0.2026 |
| 0.3108        | 1.6   | 4000  | 0.2666          | 0.1971 |
| 0.3131        | 2.0   | 5000  | 0.2173          | 0.1531 |
| 0.1796        | 2.4   | 6000  | 0.2026          | 0.1384 |
| 0.17          | 2.8   | 7000  | 0.1922          | 0.1378 |
| 0.0995        | 3.2   | 8000  | 0.1792          | 0.1206 |
| 0.0972        | 3.6   | 9000  | 0.1670          | 0.1149 |
| 0.097         | 4.0   | 10000 | 0.1545          | 0.1096 |
| 0.0553        | 4.4   | 11000 | 0.1575          | 0.1030 |
| 0.0526        | 4.8   | 12000 | 0.1431          | 0.0890 |
| 0.0299        | 5.2   | 13000 | 0.1372          | 0.0833 |
| 0.0311        | 5.6   | 14000 | 0.1258          | 0.0780 |
| 0.0295        | 6.0   | 15000 | 0.1201          | 0.0725 |
| 0.0151        | 6.4   | 16000 | 0.1229          | 0.0742 |
| 0.0163        | 6.8   | 17000 | 0.1137          | 0.0658 |
| 0.0082        | 7.2   | 18000 | 0.1142          | 0.0639 |
| 0.0092        | 7.6   | 19000 | 0.1121          | 0.0627 |
| 0.006         | 8.0   | 20000 | 0.1112          | 0.0612 |


### Framework versions

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