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whisper-small-PharmaSpeak – AI Model by DereAbdulhameed | AlphaNeural AI
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whisper-small-PharmaSpeak
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
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DereAbdulhameed/Pharma-Speak
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
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Whisper Small Medication Corpus
This model is a fine-tuned version of
openai/whisper-small
on the Pharma-Speak dataset. It achieves the following results on the evaluation set:
Loss: 0.6189
Wer: 20.0
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0
500.0
1000
0.5205
18.6047
0.0
1000.0
2000
0.5735
20.9302
0.0
1500.0
3000
0.6033
21.8605
0.0
2000.0
4000
0.6189
20.0
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
