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bert-base-finetuned-ynat – AI Model by eliza-dukim | AlphaNeural AI
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bert-base-finetuned-ynat
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transformers
pytorch
bert
text-classification
generated_from_trainer
klue
autotrain_compatible
endpoints_compatible
us
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bert-base-finetuned-ynat
This model is a fine-tuned version of
klue/bert-base
on the klue dataset. It achieves the following results on the evaluation set:
Loss: 0.3741
F1: 0.8700
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: 256
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
F1
No log
1.0
179
0.4458
0.8516
No log
2.0
358
0.3741
0.8700
0.385
3.0
537
0.3720
0.8693
0.385
4.0
716
0.3744
0.8689
0.385
5.0
895
0.3801
0.8695
Framework versions
Transformers 4.9.1
Pytorch 1.9.0+cu102
Datasets 1.11.0
Tokenizers 0.10.3
