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whisper-large-v3-English – AI Model by KhushiDS | AlphaNeural AI
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KhushiDS
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whisper-large-v3-English
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transformers
tensorboard
safetensors
automatic-speech-recognition
en
google/fleurs
openai/whisper-large-v3
finetune
apache-2.0
endpoints_compatible
us
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whisper-large-v3-English-Version2
This model is a fine-tuned version of
openai/whisper-large-v3
on the fleurs dataset. It achieves the following results on the evaluation set:
Loss: 0.1802
Wer: 5.4448
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: 3e-06
train_batch_size: 8
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: 1000
training_steps: 6000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1778
5.3333
2000
0.1887
5.6330
0.1529
10.6667
4000
0.1814
5.4587
0.1408
16.0
6000
0.1802
5.4448
Framework versions
PEFT 0.12.1.dev0
Transformers 4.45.0.dev0
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1
