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whisper-tiny-anton – AI Model by antonvinny | AlphaNeural AI
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whisper-tiny-anton
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transformers
tensorboard
onnx
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-tiny
quantized
apache-2.0
endpoints_compatible
us
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Whisper Tiny En - AntonVinny
This model is a fine-tuned version of
openai/whisper-tiny
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0000
Wer: 2.4952
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 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0001
250.0
1000
0.0002
2.5912
0.0001
500.0
2000
0.0001
2.4952
0.0
750.0
3000
0.0000
2.4952
0.0
1000.0
4000
0.0000
2.4952
Framework versions
Transformers 4.48.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
