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whisper-small-hi-exp – AI Model by Brian42521 | AlphaNeural AI
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whisper-small-hi-exp
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
hi
fsicoli/common_voice_22_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Hindi Experimental
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 22.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3003
Wer: 37.3543
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
optimizer: Use OptimizerNames.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: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.3310
0.2110
100
0.4101
45.7002
0.2631
0.4219
200
0.3488
40.9286
0.2371
0.6329
300
0.3252
39.1379
0.2116
0.8439
400
0.3058
38.1371
0.1573
1.0549
500
0.3003
37.3543
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 3.6.0
Tokenizers 0.22.2
