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whisper-kaggle-be2 – AI Model by astrung | AlphaNeural AI
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astrung
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whisper-kaggle-be2
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
audiofolder
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-kaggle-be2
This model is a fine-tuned version of
openai/whisper-small
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.3317
Wer: 45.6225
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: 500
training_steps: 4000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0777
3.33
1000
0.1892
50.8835
0.0108
6.67
2000
0.2534
48.8755
0.0015
10.0
3000
0.3003
45.9839
0.0002
13.33
4000
0.3317
45.6225
Framework versions
Transformers 4.33.0.dev0
Pytorch 2.0.0
Datasets 2.14.4.dev0
Tokenizers 0.13.3
