---
library_name: transformers
language:
- jv
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- javanese
- asr
- generated_from_trainer
datasets:
- jv_id_asr_split
metrics:
- wer
model-index:
- name: Whisper Tiny Java
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: jv_id_asr_split
      type: jv_id_asr_split
      config: jv_id_asr_source
      split: None
      args: jv_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 0.6471586421539112
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the jv_id_asr_split dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2792
- Wer: 0.6472

## 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: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.528         | 0.8643 | 500  | 0.4467          | 0.4770 |
| 0.3702        | 1.7277 | 1000 | 0.3424          | 0.5528 |
| 0.2988        | 2.5946 | 1500 | 0.3031          | 0.5552 |
| 0.2607        | 3.4581 | 2000 | 0.2859          | 0.6485 |
| 0.2481        | 4.3215 | 2500 | 0.2792          | 0.6472 |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.4.0
- Tokenizers 0.21.1