---
library_name: transformers
language:
- jav
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- SLR41_35
metrics:
- wer
model-index:
- name: Whisper Small Java
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: SLR Javanenese 41_35
      type: SLR41_35
      args: 'config: java, split: train, test'
    metrics:
    - type: wer
      value: 29.24663420223432
      name: Wer
---

<!-- 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 Small Java

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR Javanenese 41_35 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4200
- Wer: 29.2466

## 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: 16
- eval_batch_size: 8
- seed: 42
- 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4922        | 0.16  | 100  | 0.6047          | 37.4678 |
| 0.435         | 0.32  | 200  | 0.5572          | 35.9424 |
| 0.5688        | 0.48  | 300  | 0.5090          | 33.5649 |
| 0.4779        | 0.64  | 400  | 0.4799          | 31.8390 |
| 0.4247        | 0.8   | 500  | 0.4540          | 30.8364 |
| 0.42          | 0.96  | 600  | 0.4368          | 30.2492 |
| 0.2276        | 1.12  | 700  | 0.4330          | 29.6333 |
| 0.2137        | 1.28  | 800  | 0.4264          | 29.5832 |
| 0.236         | 1.44  | 900  | 0.4215          | 29.2395 |
| 0.1971        | 1.6   | 1000 | 0.4200          | 29.2466 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1