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whisper-base-ClearSpeak – AI Model by recyclebin12331 | AlphaNeural AI
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whisper-base-ClearSpeak
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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whisper-base-ClearSpeak
This model is a fine-tuned version of
openai/whisper-base
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.0543
eval_wer: 1.9591
eval_runtime: 149.6409
eval_samples_per_second: 3.555
eval_steps_per_second: 0.448
epoch: 12.4060
step: 1650
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-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
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: 100
training_steps: 2000
mixed_precision_training: Native AMP
Framework versions
Transformers 5.4.0
Pytorch 2.10.0+cu128
Datasets 4.8.4
Tokenizers 0.22.2
