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BaseC – AI Model by Soupis | AlphaNeural AI
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Soupis
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BaseC
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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Whisper-opus
This model is a fine-tuned version of
openai/whisper-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0166
Wer: 21.6675
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: 2e-05
train_batch_size: 24
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: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0174
0.3676
500
0.0201
24.7213
0.0207
0.7353
1000
0.0183
23.1944
0.0152
1.1029
1500
0.0166
21.6675
Framework versions
Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1
