Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
vanilla-whisper-medium – AI Model by jethrowang | AlphaNeural AI
You can deploy this model and start earning money today!
jethrowang
/
vanilla-whisper-medium
like
0
tensorboard
safetensors
whisper
generated_from_trainer
zh
formospeech/hat_asr_aligned
openai/whisper-medium
finetune
apache-2.0
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
Whisper Medium Hakka Condenser
This model is a fine-tuned version of
openai/whisper-medium
on the HAT ASR Aligned dataset. It achieves the following results on the evaluation set:
Loss: 0.0401
Cer: 1.8101
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: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1521
training_steps: 15215
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.0328
0.9997
3043
0.0681
4.6235
0.0135
1.9993
6086
0.0515
2.8839
0.0045
2.9990
9129
0.0440
1.9904
0.0028
3.9987
12172
0.0403
2.0760
0.0007
4.9984
15215
0.0401
1.8101
Framework versions
Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
