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whisper-model – AI Model by danial1245 | AlphaNeural AI
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whisper-model
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-model
This model is a fine-tuned version of
openai/whisper-small
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.9859
eval_model_preparation_time: 0.0
eval_wer: 65.4080
eval_runtime: 159.814
eval_samples_per_second: 1.176
eval_steps_per_second: 0.15
epoch: 5.9701
step: 800
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 10
mixed_precision_training: Native AMP
Framework versions
Transformers 5.15.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
