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whisper-large-v3-turbo-finetune-syn-v1 – AI Model by Endy2001 | AlphaNeural AI
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whisper-large-v3-turbo-finetune-syn-v1
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large-v3-turbo
finetune
mit
endpoints_compatible
us
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whisper-large-v3-turbo-finetune-syn-v1
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:
eval_loss: 1.1287
eval_wer: 0.0449
eval_runtime: 10.2734
eval_samples_per_second: 3.407
eval_steps_per_second: 0.195
epoch: 10.0
step: 10
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: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
training_steps: 20000
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
