luke-base_finetuned_conll2003 – AI Model by lambdavi | AlphaNeural AI

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lambdavi/
luke-base_finetuned_conll2003

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token-classification

generated_from_trainer

studio-ousia/luke-base

autotrain_compatible

endpoints_compatible

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luke-base_finetuned_conll2003

This model is a fine-tuned version of studio-ousia/luke-base on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0959
F1-type-match: 0.7530
F1-partial: 0.7885
F1-strict: 0.7477
F1-exact: 0.7828

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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-type-match	F1-partial	F1-strict	F1-exact
No log	1.0	219	0.0796	0.3002	0.3178	0.2969	0.3146
0.1554	2.0	439	0.0724	0.3889	0.4078	0.3859	0.4048
0.0256	3.0	658	0.0832	0.5340	0.5610	0.5300	0.5568
0.0124	4.0	878	0.0918	0.6875	0.7207	0.6826	0.7156
0.0062	4.99	1095	0.0959	0.7530	0.7885	0.7477	0.7828

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.14.1