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whisper-medium-medical – AI Model by jilangdi | AlphaNeural AI
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whisper-medium-medical
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
yashtiwari/PaulMooney-Medical-ASR-Data
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Medium Medical
This model is a fine-tuned version of
openai/whisper-medium
on the Medical ASR dataset. It achieves the following results on the evaluation set:
Loss: 0.0995
Wer: 12.4065
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: 8
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: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.7532
0.1357
100
0.2695
13.0099
0.2155
0.2714
200
0.2053
9.8238
0.2392
0.4071
300
0.1567
8.9549
0.151
0.5427
400
0.1159
6.9273
0.1439
0.6784
500
0.0995
12.4065
Framework versions
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0
