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whisper-large-v3-turbo-test – AI Model by Endy2001 | AlphaNeural AI

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Endy2001/
whisper-large-v3-turbo-test

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automatic-speech-recognition

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openai/whisper-large-v3-turbo

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whisper-large-v3-turbo-test

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: 0.9067
eval_wer: 0.0229
eval_runtime: 8.8041
eval_samples_per_second: 3.975
eval_steps_per_second: 0.227
epoch: 30.0
step: 30

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