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whisper_ami_finetuned – AI Model by gngpostalsrvc | AlphaNeural AI
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whisper_ami_finetuned
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper_ami_finetuned
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: 1.0307
Wer: 28.8275
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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.3847
1.0
649
0.7598
29.7442
0.6419
2.0
1298
0.7462
28.5128
0.4658
3.0
1947
0.7728
28.7454
0.154
4.0
2596
0.8675
29.2516
0.0852
5.0
3245
1.0307
28.8275
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2
