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whisper-finetuned-v3_3e_augment – AI Model by tranha1412 | AlphaNeural AI
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whisper-finetuned-v3_3e_augment
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large-v3-turbo
finetune
mit
endpoints_compatible
us
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whisper-finetuned-v3_3e_augment
This model is a fine-tuned version of
openai/whisper-large-v3-turbo
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0544
Wer: 49.8630
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
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: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1249
1.0
1179
0.1154
66.6096
0.0584
2.0
2358
0.0688
54.9658
0.0201
3.0
3537
0.0544
49.8630
Framework versions
Transformers 4.51.3
Pytorch 2.7.0+cu126
Datasets 3.5.1
Tokenizers 0.21.1
