---
library_name: transformers
language:
- jv
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper
- javanese
- asr
- generated_from_trainer
datasets:
- jv_id_asr_split
metrics:
- wer
model-index:
- name: bagasshw/whisper-large-v2-jv-filtered
  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: validation
      args: jv_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 6.3495792761984315
---

<!-- 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. -->

# bagasshw/whisper-large-v2-jv-filtered

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the jv_id_asr_split dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0756
- Wer: 6.3496

## 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: 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_steps: 500
- training_steps: 60000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2396        | 0.1535 | 5000  | 0.2416          | 19.2376 |
| 0.1912        | 0.3071 | 10000 | 0.2009          | 16.2781 |
| 0.1744        | 0.4606 | 15000 | 0.1687          | 14.4586 |
| 0.1448        | 0.6142 | 20000 | 0.1494          | 12.9593 |
| 0.138         | 0.7677 | 25000 | 0.1333          | 11.8420 |
| 0.1312        | 0.9213 | 30000 | 0.1192          | 10.7587 |
| 0.0605        | 1.0748 | 35000 | 0.1096          | 9.9808  |
| 0.0524        | 1.2284 | 40000 | 0.1022          | 9.3473  |
| 0.0506        | 1.3819 | 45000 | 0.0929          | 8.2091  |
| 0.0476        | 1.5355 | 50000 | 0.0859          | 7.7627  |
| 0.0389        | 1.6890 | 55000 | 0.0795          | 6.7298  |
| 0.0357        | 1.8426 | 60000 | 0.0756          | 6.3496  |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.7.0+cu128
- Datasets 2.18.0
- Tokenizers 0.21.1