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whisper-medium-finetuned – AI Model by manushya-ai | AlphaNeural AI
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whisper-medium-finetuned
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium-finetuned
This model is a fine-tuned version of
openai/whisper-medium
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 0.0120
eval_wer: 28.7151
eval_runtime: 98.274
eval_samples_per_second: 0.407
eval_steps_per_second: 0.407
epoch: 9.0
step: 540
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: 2e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 30
num_epochs: 10
Framework versions
Transformers 4.48.0
Pytorch 2.9.0+cu128
Datasets 4.4.1
Tokenizers 0.21.4
