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whisper-medium-ft-5000 – AI Model by adityarra07 | AlphaNeural AI
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whisper-medium-ft-5000
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium-ft-5000
This model is a fine-tuned version of
openai/whisper-medium
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2673
Wer: 10.3673
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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.5238
1.0
313
0.2389
12.2734
0.1035
2.0
626
0.2360
11.2041
0.0381
3.0
939
0.2349
10.7857
0.0134
4.0
1252
0.2512
10.5532
0.0039
5.0
1565
0.2611
10.2278
0.0013
6.0
1878
0.2673
10.3673
Framework versions
Transformers 4.33.1
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3
