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whisper-small-hi – AI Model by perchaos | AlphaNeural AI
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Whisper Small Hindi - Fine-tuned
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.5177
Wer: 33.1880
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use adamw_torch_fused 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0392
4.8802
1000
0.3348
34.2504
0.0026
9.7579
2000
0.4595
33.9499
0.0002
14.6357
3000
0.5030
33.1034
0.0002
19.5134
4000
0.5177
33.1880
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.22.0
