layoutlmv3-finetuned-funsd – AI Model by smitbutle | AlphaNeural AI

You can deploy this model and start earning money today!

smitbutle/
layoutlmv3-finetuned-funsd

like

0

token-classification

generated_from_trainer

microsoft/layoutlmv3-base

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

Views

No views yet

layoutlmv3-finetuned-funsd

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

Loss: 0.5984
Precision: 0.7468
Recall: 0.8028
F1: 0.7738
Accuracy: 0.8189

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: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.67	100	1.0197	0.5025	0.5981	0.5462	0.6622
No log	1.34	200	0.6833	0.6203	0.7238	0.6680	0.7608
No log	2.01	300	0.6237	0.6401	0.7794	0.7030	0.7846
No log	2.68	400	0.6028	0.6892	0.7392	0.7133	0.7771
0.8343	3.36	500	0.5948	0.7175	0.7884	0.7512	0.7991
0.8343	4.03	600	0.5953	0.7135	0.8028	0.7555	0.7961
0.8343	4.7	700	0.5925	0.7354	0.7953	0.7642	0.8174
0.8343	5.37	800	0.6055	0.7397	0.7933	0.7656	0.8134
0.8343	6.04	900	0.5940	0.7535	0.8077	0.7797	0.8199
0.3468	6.71	1000	0.5984	0.7468	0.8028	0.7738	0.8189

Framework versions

Transformers 4.35.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.14.1