|
--- |
|
library_name: transformers |
|
language: |
|
- jv |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- whisper |
|
- javanese |
|
- asr |
|
- generated_from_trainer |
|
datasets: |
|
- jv_id_asr_split |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Tiny Java |
|
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: None |
|
args: jv_id_asr_source |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.6471586421539112 |
|
--- |
|
|
|
<!-- 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 |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the jv_id_asr_split dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2792 |
|
- Wer: 0.6472 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 256 |
|
- 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: 2500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:------:| |
|
| 0.528 | 0.8643 | 500 | 0.4467 | 0.4770 | |
|
| 0.3702 | 1.7277 | 1000 | 0.3424 | 0.5528 | |
|
| 0.2988 | 2.5946 | 1500 | 0.3031 | 0.5552 | |
|
| 0.2607 | 3.4581 | 2000 | 0.2859 | 0.6485 | |
|
| 0.2481 | 4.3215 | 2500 | 0.2792 | 0.6472 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.50.0.dev0 |
|
- Pytorch 2.6.0+cu126 |
|
- Datasets 3.4.0 |
|
- Tokenizers 0.21.1 |
|
|
