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repo_name – AI Model by aoome123 | AlphaNeural AI
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
ko
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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ft_model
This model is a fine-tuned version of
openai/whisper-base
on the important dataset. It achieves the following results on the evaluation set:
Loss: 1.0252
Cer: 36.9125
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: 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
Cer
0.5019
2.81
1000
0.8572
69.8151
0.1416
5.62
2000
0.9210
41.5237
0.0244
8.43
3000
0.9906
37.2912
0.0139
11.24
4000
1.0252
36.9125
Framework versions
Transformers 4.35.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
