doc_classification

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

• Loss: 0.0056
• Precision: 1.0
• Recall: 1.0
• F1: 1.0
• Accuracy: 1.0

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: 2
• eval_batch_size: 2
• 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	8.33	100	0.3533	0.4147	0.3516	0.3805	0.8964
No log	16.67	200	0.0993	0.884	0.8633	0.8735	0.9782
No log	25.0	300	0.0338	0.9882	0.9805	0.9843	0.9977
No log	33.33	400	0.0173	0.9961	0.9922	0.9941	0.9992
0.238	41.67	500	0.0109	1.0	1.0	1.0	1.0
0.238	50.0	600	0.0081	1.0	1.0	1.0	1.0
0.238	58.33	700	0.0068	1.0	1.0	1.0	1.0
0.238	66.67	800	0.0061	1.0	1.0	1.0	1.0
0.238	75.0	900	0.0057	1.0	1.0	1.0	1.0
0.0136	83.33	1000	0.0056	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.2