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whisper-small-ml-en-finetuned – AI Model by Be-win | AlphaNeural AI
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Be-win
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whisper-small-ml-en-finetuned
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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-small-finetuned-ml-en
This model is a fine-tuned version of
openai/whisper-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.6611
Wer: 153.5124
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: 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.5079
1.4327
500
1.7015
114.2188
1.0223
2.8653
1000
1.5594
120.3721
0.4114
4.2980
1500
1.6128
154.1043
0.257
5.7307
2000
1.6611
153.5124
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.1.0
Tokenizers 0.22.0
