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whisper-small-gs_test – AI Model by antonvinny | AlphaNeural AI
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whisper-small-gs_test
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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 dont use
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: 0.2379
Wer: 8.0357
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: 3e-05
train_batch_size: 16
eval_batch_size: 8
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: 50
training_steps: 400
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0001
25.0
100
0.2405
8.0357
0.0001
50.0
200
0.2371
8.0357
0.0001
75.0
300
0.2374
8.0357
0.0
100.0
400
0.2379
8.0357
Framework versions
Transformers 4.48.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
