Beta
Explore
Marketplace
Neural Labs
Playground
Wallet
Docs
whisper-vi-finetune – AI Model by uknhu | AlphaNeural AI | AlphaNeural AI
You can deploy this model and start earning money today!
uknhu
/
whisper-vi-finetune
like
0
peft
tensorboard
safetensors
adapter
lora
transformers
openai/whisper-small
apache-2.0
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
whisper-vi-finetune
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.0505
Bleu: 15.8588
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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 200
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
1.5119
1.0
1875
2.0235
15.8480
1.4738
2.0
3750
2.0297
15.9338
1.4504
3.0
5625
2.0404
15.7693
1.3735
4.0
7500
2.0505
15.8588
Framework versions
PEFT 0.16.0
Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.21.2
