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repo_name – AI Model by Jpep26 | AlphaNeural AI
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
ko
Jpep26/AfterProcessing
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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This model is a fine-tuned version of
openai/whisper-base
on the AfterProcessing dataset. It achieves the following results on the evaluation set:
Loss: 0.9167
Cer: 0.8486
Wer: 0.7054
Mean: 0.7770
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: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
Wer
Mean
2.9457
0.6410
50
2.6739
0.5791
0.8056
0.6923
1.7821
1.2821
100
1.6827
0.4622
0.6561
0.5592
1.2153
1.9231
150
1.1411
0.4216
0.6022
0.5119
0.8636
2.5641
200
0.9167
0.8486
0.7054
0.7770
Framework versions
Transformers 4.45.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.20.0
Tokenizers 0.19.1
