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whisper-small-chinese – AI Model by ciderstt | AlphaNeural AI
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whisper-small-chinese
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
zh
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.4206
Wer: 84.0991
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 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
0.4416
1.3141
1000
0.5228
89.7780
0.2359
2.6281
2000
0.4207
86.8353
0.1247
3.9422
3000
0.4052
84.7186
0.0468
5.2562
4000
0.4206
84.0991
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1
