This model is a fine-tuned version of nielsr/lilt-roberta-en-base on the funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:

Loss: 1.6552
Precision: 0.8762
Recall: 0.8857
F1: 0.8809
Accuracy: 0.8068

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: 5e-05
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_steps: 0.1
training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	5.26	100	1.1789	0.8506	0.8485	0.8495	0.7869
No log	10.53	200	1.2382	0.8360	0.8788	0.8569	0.7970
No log	15.79	300	1.3766	0.8557	0.8897	0.8724	0.7909
No log	21.05	400	1.5590	0.8368	0.8763	0.8561	0.7792
0.04	26.32	500	1.4379	0.8562	0.8813	0.8685	0.7992
0.04	31.58	600	1.5397	0.8593	0.8947	0.8766	0.8054
0.04	36.84	700	1.6132	0.8621	0.8723	0.8672	0.7933
0.04	42.11	800	1.6483	0.8566	0.8872	0.8716	0.7777
0.04	47.37	900	1.6593	0.8641	0.8813	0.8726	0.7895
0.0044	52.63	1000	1.6704	0.8595	0.8718	0.8656	0.7925
0.0044	57.89	1100	1.6795	0.8495	0.8803	0.8646	0.7748
0.0044	63.16	1200	1.5515	0.8604	0.8912	0.8755	0.7991
0.0044	68.42	1300	1.6665	0.8573	0.8867	0.8718	0.7821
0.0044	73.68	1400	1.5893	0.8604	0.8877	0.8738	0.7895
0.0008	78.95	1500	1.5613	0.8603	0.8872	0.8736	0.8123
0.0008	84.21	1600	1.5853	0.8521	0.8872	0.8693	0.8040
0.0008	89.47	1700	1.6539	0.8707	0.8833	0.8769	0.8077
0.0008	94.74	1800	1.6634	0.8787	0.8813	0.8800	0.8079
0.0008	100.0	1900	1.6534	0.8810	0.8862	0.8836	0.8073
0.0004	105.26	2000	1.6552	0.8762	0.8857	0.8809	0.8068

Framework versions

Transformers 4.23.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.13.0

nielsr/lilt-roberta-en-base-finetuned-funsd

lilt-roberta-en-base-finetuned-funsd

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nielsr/
lilt-roberta-en-base-finetuned-funsd