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whisper-medium-ln-ojpl-2 – AI Model by BrainTheos | AlphaNeural AI
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BrainTheos
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whisper-medium-ln-ojpl-2
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
BrainTheos/ojpl
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-medium-ln-ojpl-2
This model is a fine-tuned version of
openai/whisper-medium
on the BrainTheos/ojpl dataset. It achieves the following results on the evaluation set:
Loss: 1.1202
Wer Ortho: 35.8309
Wer: 0.2901
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 4000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0172
23.19
1000
0.9966
41.9139
0.3407
0.0053
46.38
2000
1.0716
37.0920
0.2996
0.0034
69.57
3000
1.1329
36.0163
0.2850
0.0021
92.75
4000
1.1202
35.8309
0.2901
Framework versions
Transformers 4.32.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3
