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whisper-medium-yue-continuous – AI Model by 6x16 | AlphaNeural AI
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whisper-medium-yue-continuous
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
yue
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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self-trained Whisper-Medium Yue model (to be fine-tuned by other datasets) #JL
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2796
Cer: 8.3321
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
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.0187
5.5556
1000
0.2198
9.1962
0.0006
11.1111
2000
0.2458
8.8610
0.0001
16.6667
3000
0.2670
8.4587
0.0001
22.2222
4000
0.2757
8.3544
0.0001
27.7778
5000
0.2796
8.3321
Framework versions
Transformers 4.52.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1
