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whisper-base-hi – AI Model by atulksingh | AlphaNeural AI
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whisper-base-hi
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
atulksingh/mypin-voice-dataset
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Base myPin
This model is a fine-tuned version of
openai/whisper-base
on the Domain Based voice dataset. It achieves the following results on the evaluation set:
Loss: 0.0769
Wer: 34.5238
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-06
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use 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: 100
training_steps: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2114
36.3636
500
0.2534
100.0
0.0186
72.7273
1000
0.0846
36.3095
0.0067
109.0909
1500
0.0769
34.5238
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
