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kcbert-base-finetuned-code-classification-mid – AI Model by JUNstats | AlphaNeural AI
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JUNstats
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kcbert-base-finetuned-code-classification-mid
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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kcbert-base-finetuned-code-classification-mid
This model is a fine-tuned version of
beomi/kcbert-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2025
Accuracy: 0.9485
F1: 0.9474
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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.2959
1.0
4931
0.2158
0.9442
0.9428
0.1656
2.0
9862
0.2025
0.9485
0.9474
Framework versions
Transformers 4.28.1
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.13.3
