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model_checkpoint – AI Model by 5p33ch3xpr | AlphaNeural AI
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5p33ch3xpr
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model_checkpoint
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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model_checkpoint
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3509
Wer: 69.8851
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: 12
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
0.0805
1.88
1000
0.2634
74.4828
0.0242
3.77
2000
0.2649
73.1034
0.0068
5.65
3000
0.3314
72.4138
0.0005
7.53
4000
0.3509
69.8851
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
