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whipser-small-hi – AI Model by annaissune | AlphaNeural AI
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whipser-small-hi
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whipser-small-hi
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: 0.5848
Wer: 302.5
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: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.072
15.38
200
0.5236
128.5
0.0005
30.77
400
0.5438
216.0
0.0002
46.15
600
0.5696
204.0
0.0001
61.54
800
0.5810
294.5
0.0001
76.92
1000
0.5848
302.5
Framework versions
Transformers 4.29.0.dev0
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
