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asr_sunda_result_full – AI Model by bagasshw | AlphaNeural AI
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asr_sunda_result_full
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
sundanese
asr
generated_from_trainer
su
su_id_asr_split
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Tiny Sunda
This model is a fine-tuned version of
openai/whisper-tiny
on the su_id_asr_split dataset. It achieves the following results on the evaluation set:
Loss: 0.4974
Wer: 0.5419
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: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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: 30
training_steps: 150
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
2.8761
0.0219
30
1.2365
0.7810
0.9096
0.0438
60
0.7216
0.5673
0.6491
0.0657
90
0.5795
0.5316
0.5444
0.0876
120
0.5178
0.5609
0.4887
0.1095
150
0.4975
0.5418
Framework versions
Transformers 4.50.0.dev0
Pytorch 2.6.0+cu126
Datasets 3.3.2
Tokenizers 0.21.0
