---
library_name: transformers
language:
- jv
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- javanese
- asr
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-Tiny-Java-v7
  results: []
---

<!-- 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-v7

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6090
- Wer: 0.5104

## 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: 8
- eval_batch_size: 4
- 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_ratio: 0.1
- training_steps: 50000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.9973        | 8.0   | 1000  | 1.0428          | 0.6821 |
| 0.3139        | 16.0  | 2000  | 0.8733          | 0.6234 |
| 0.0988        | 24.0  | 3000  | 0.8925          | 0.6347 |
| 0.0499        | 32.0  | 4000  | 0.9389          | 0.6149 |
| 0.0349        | 40.0  | 5000  | 0.9879          | 0.6206 |
| 0.0246        | 48.0  | 6000  | 1.0245          | 0.4681 |
| 0.0164        | 56.0  | 7000  | 1.1032          | 0.4715 |
| 0.0118        | 64.0  | 8000  | 1.1389          | 0.5985 |
| 0.0094        | 72.0  | 9000  | 1.1457          | 0.5793 |
| 0.0086        | 80.0  | 10000 | 1.1854          | 0.5375 |
| 0.0067        | 88.0  | 11000 | 1.2372          | 0.4664 |
| 0.005         | 96.0  | 12000 | 1.2564          | 0.4992 |
| 0.0043        | 104.0 | 13000 | 1.2725          | 0.4478 |
| 0.0039        | 112.0 | 14000 | 1.3331          | 0.5308 |
| 0.0036        | 120.0 | 15000 | 1.3492          | 0.6036 |
| 0.0028        | 128.0 | 16000 | 1.3910          | 0.4551 |
| 0.0034        | 136.0 | 17000 | 1.4366          | 0.4907 |
| 0.0024        | 144.0 | 18000 | 1.3797          | 0.6126 |
| 0.0019        | 152.0 | 19000 | 1.4368          | 0.5229 |
| 0.0017        | 160.0 | 20000 | 1.4499          | 0.5980 |
| 0.0014        | 168.0 | 21000 | 1.4369          | 0.5940 |
| 0.0015        | 176.0 | 22000 | 1.4615          | 0.5308 |
| 0.001         | 184.0 | 23000 | 1.4453          | 0.4986 |
| 0.0009        | 192.0 | 24000 | 1.4906          | 0.5471 |
| 0.0007        | 200.0 | 25000 | 1.4574          | 0.4941 |
| 0.0011        | 208.0 | 26000 | 1.4995          | 0.4647 |
| 0.0007        | 216.0 | 27000 | 1.5195          | 0.5155 |
| 0.0011        | 224.0 | 28000 | 1.4928          | 0.5483 |
| 0.0011        | 232.0 | 29000 | 1.5243          | 0.5144 |
| 0.0007        | 240.0 | 30000 | 1.5805          | 0.4884 |
| 0.0005        | 248.0 | 31000 | 1.5294          | 0.5116 |
| 0.0005        | 256.0 | 32000 | 1.5940          | 0.4975 |
| 0.0003        | 264.0 | 33000 | 1.5760          | 0.5003 |
| 0.0004        | 272.0 | 34000 | 1.5940          | 0.4873 |
| 0.0003        | 280.0 | 35000 | 1.6010          | 0.4681 |
| 0.0004        | 288.0 | 36000 | 1.5837          | 0.4845 |
| 0.0006        | 296.0 | 37000 | 1.5839          | 0.4794 |
| 0.0002        | 304.0 | 38000 | 1.5652          | 0.4754 |
| 0.0003        | 312.0 | 39000 | 1.6083          | 0.4833 |
| 0.0002        | 320.0 | 40000 | 1.5750          | 0.5189 |
| 0.0004        | 328.0 | 41000 | 1.6199          | 0.5980 |
| 0.0001        | 336.0 | 42000 | 1.5783          | 0.5353 |
| 0.0001        | 344.0 | 43000 | 1.5898          | 0.5099 |
| 0.0005        | 352.0 | 44000 | 1.6005          | 0.5833 |
| 0.0002        | 360.0 | 45000 | 1.5903          | 0.4873 |
| 0.0002        | 368.0 | 46000 | 1.6196          | 0.5150 |
| 0.0001        | 376.0 | 47000 | 1.6212          | 0.5251 |
| 0.0002        | 384.0 | 48000 | 1.6180          | 0.5539 |
| 0.0001        | 392.0 | 49000 | 1.6104          | 0.4963 |
| 0.0001        | 400.0 | 50000 | 1.6090          | 0.5104 |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.7.0+cu128
- Datasets 2.16.0
- Tokenizers 0.21.1