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whisper-medium-ckb – AI Model by roseman | AlphaNeural AI
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roseman
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whisper-medium-ckb
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper-medium-ckb
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: 0.2977
Wer: 31.3503
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: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1833
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.27
1.03
366
0.2722
43.9177
0.1498
2.07
732
0.2354
36.2845
0.0538
3.1
1098
0.2422
33.6539
0.0168
4.14
1464
0.2717
32.3842
0.0025
6.0
1830
0.2977
31.3503
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.7.1
Tokenizers 0.13.2
