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luke-base-paper-setup – AI Model by TheNewPing | AlphaNeural AI
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luke-base-paper-setup
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transformers
safetensors
luke
multiple-choice
generated_from_trainer
studio-ousia/luke-base
finetune
apache-2.0
endpoints_compatible
us
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luke-base-paper-setup
This model is a fine-tuned version of
studio-ousia/luke-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3800
Accuracy: 0.8426
Precision: 0.8465
Recall: 0.8370
F1: 0.8417
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.5192
1.0
1074
0.4464
0.8063
0.8263
0.7756
0.8001
0.3708
2.0
2148
0.3782
0.8315
0.8365
0.8241
0.8303
0.3191
3.0
3222
0.3800
0.8426
0.8465
0.8370
0.8417
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
