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---
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
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