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whisper-medium-cv-fleurs-tr-3k – AI Model by sgangireddy | AlphaNeural AI
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whisper-medium-cv-fleurs-tr-3k
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
whisper-event
generated_from_trainer
apache-2.0
endpoints_compatible
us
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Model card
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openai/whisper-medium
This model is a fine-tuned version of
openai/whisper-medium
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2406
Wer: 10.0333
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: 64
eval_batch_size: 32
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: 3000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0241
1.06
1000
0.1996
10.4543
0.009
2.12
2000
0.2156
10.1152
0.0045
3.19
3000
0.2406
10.0333
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2
