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whisper-large-v3.vi – AI Model by Prateekjain24 | AlphaNeural AI | AlphaNeural AI
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whisper-large-v3.vi
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
vi
google/fleurs
openai/whisper-large-v3
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Large V3 Vi - Prateek Jain
This model is a fine-tuned version of
openai/whisper-large-v3
on the google/fleurs dataset. It achieves the following results on the evaluation set:
Loss: 0.2355
Wer: 218.8330
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
training_steps: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0148
2.66
500
0.2193
80.1012
0.0014
5.32
1000
0.2275
247.5556
0.0004
7.98
1500
0.2355
218.8330
Framework versions
Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1
