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whisper-medium-yo – AI Model by thabel | AlphaNeural AI
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whisper-medium-yo
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
dv
mozilla-foundation/common_voice_13_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Dv - Sanchit Gandhi
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
Loss: 0.8186
Wer Ortho: 69.8365
Wer: 47.3308
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: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.061
5.8824
500
0.8186
69.8365
47.3308
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
