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whisper-finetuned-v3_30e_augment_new – AI Model by tranha | AlphaNeural AI
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whisper-finetuned-v3_30e_augment_new
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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_30e_augment_new
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
epoch: 30.0
eval_cer: 27.6678
eval_loss: 0.1077
eval_runtime: 688.6506
eval_samples_per_second: 0.839
eval_steps_per_second: 0.42
eval_wer: 52.3943
step: 58500
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 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: 500
num_epochs: 30
mixed_precision_training: Native AMP
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 2.18.0
Tokenizers 0.22.2
