legal-luke-base-ner – AI Model by lambdavi | AlphaNeural AI

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lambdavi/
legal-luke-base-ner

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token-classification

generated_from_trainer

studio-ousia/luke-base

autotrain_compatible

endpoints_compatible

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legal-luke-base-ner

This model is a fine-tuned version of studio-ousia/luke-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0153
F1-type-match: 0.9297
F1-partial: 0.9197
F1-strict: 0.8794
F1-exact: 0.8891

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: 0.0001
train_batch_size: 8
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_ratio: 0.06
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1-type-match	F1-partial	F1-strict	F1-exact
0.021	1.0	1375	0.0219	0.8297	0.8176	0.7238	0.7525
0.0132	2.0	2750	0.0156	0.8841	0.8722	0.7943	0.8166
0.0087	3.0	4125	0.0155	0.8901	0.8796	0.8271	0.8374
0.0052	4.0	5500	0.0153	0.9190	0.9100	0.8633	0.8750
0.0035	5.0	6875	0.0153	0.9297	0.9197	0.8794	0.8891

Framework versions

Transformers 4.36.0
Pytorch 2.0.0
Datasets 2.17.1
Tokenizers 0.15.0