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whisper-med-yo – AI Model by jacccc | AlphaNeural AI
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whisper-med-yo
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
yo
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Med Yo
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 1.1322
Wer: 55.7814
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
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
0.026
6.8259
1000
0.8551
58.5043
0.0029
13.6519
2000
1.0240
56.1739
0.0003
20.4778
3000
1.1121
55.4286
0.0002
27.3038
4000
1.1322
55.7814
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
