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whisper_small_vi500 – AI Model by anhphuong | AlphaNeural AI
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whisper_small_vi500
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
vi
vi_500/80k
model-index
endpoints_compatible
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Whisper Small Vi - Anh Phuong
This model is a fine-tuned version of
openai/whisper-small-vi-v2
on the vi 500 dataset. It achieves the following results on the evaluation set:
Loss: 0.1002
Wer: 5.8290
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: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
0.1638
0.2
1000
0.1707
9.6824
0.1233
0.4
2000
0.1302
7.4792
0.1063
0.6
3000
0.1097
6.4330
0.0962
0.8
4000
0.1002
5.8290
Framework versions
Transformers 4.43.3
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
