---
library_name: transformers
language:
- jav
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- SLR35
metrics:
- wer
model-index:
- name: Whisper Small Java
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: SLR Javanenese
      type: SLR35
      args: 'config: java, split: train, test'
    metrics:
    - name: Wer
      type: wer
      value: 38.373095717160105
---

<!-- 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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9356
- Wer: 38.3731

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- 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_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8832        | 0.1   | 100  | 0.9373          | 51.7965 |
| 0.3579        | 1.075 | 200  | 0.9986          | 51.4516 |
| 0.2348        | 2.05  | 300  | 0.9892          | 46.0765 |
| 0.1397        | 3.025 | 400  | 1.0404          | 47.0250 |
| 0.0836        | 3.125 | 500  | 0.9862          | 46.9531 |
| 0.0515        | 4.1   | 600  | 1.0148          | 42.2248 |
| 0.0222        | 5.075 | 700  | 0.9917          | 40.2846 |
| 0.0191        | 6.05  | 800  | 0.9665          | 39.3360 |
| 0.0078        | 7.025 | 900  | 0.9541          | 39.0486 |
| 0.0009        | 7.125 | 1000 | 0.9356          | 38.3731 |


### Framework versions

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