metadata
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- arkanalexei/bisix_su_id_reset
metrics:
- wer
model-index:
- name: 'BisiX: Sundanese Whisper (Reset Params)'
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: SU ID ASR
type: arkanalexei/bisix_su_id_reset
config: su_id_asr_source
split: validation
args: su_id_asr_source
metrics:
- name: Wer
type: wer
value: 100
BisiX: Sundanese Whisper (Reset Params)
This model is a fine-tuned version of openai/whisper-tiny.en on the SU ID ASR dataset. It achieves the following results on the evaluation set:
- Loss: 10.7367
- Wer: 100.0
- Cer: 100.0
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Cer |
|---|---|---|---|---|---|
| 10.8526 | 1.1765 | 100 | 10.8491 | 100.9708 | 81.1835 |
| 10.8392 | 2.3529 | 200 | 10.8336 | 1808.6292 | 800.3308 |
| 10.8194 | 3.5294 | 300 | 10.8165 | 2677.0607 | 1196.5347 |
| 10.8034 | 4.7059 | 400 | 10.7992 | 207.8742 | 83.6906 |
| 10.7876 | 5.8824 | 500 | 10.7815 | 148.4494 | 78.2801 |
| 10.7684 | 7.0588 | 600 | 10.7662 | 110.9303 | 77.7046 |
| 10.7567 | 8.2353 | 700 | 10.7537 | 93.9326 | 75.0677 |
| 10.7473 | 9.4118 | 800 | 10.7442 | 100.0 | 100.0 |
| 10.7389 | 10.5882 | 900 | 10.7386 | 100.0 | 100.0 |
| 10.7366 | 11.7647 | 1000 | 10.7367 | 100.0 | 100.0 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0