metadata

license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: layoutlmv3-testCUSTOMds20_02
    results: []

layoutlmv3-testCUSTOMds20_02

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1298
Precision: 0.8546
Recall: 0.8362
F1: 0.8453
Accuracy: 0.9807

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	1.25	100	0.0624	0.8578	0.8578	0.8578	0.9837
No log	2.5	200	0.0858	0.8603	0.8491	0.8547	0.9814
No log	3.75	300	0.0826	0.9062	0.875	0.8904	0.9859
No log	5.0	400	0.0940	0.9018	0.8707	0.8860	0.9851
0.0658	6.25	500	0.1237	0.8502	0.8319	0.8410	0.9807
0.0658	7.5	600	0.1125	0.9045	0.8578	0.8805	0.9844
0.0658	8.75	700	0.1252	0.8448	0.8448	0.8448	0.9799
0.0658	10.0	800	0.1156	0.8678	0.8491	0.8584	0.9829
0.0658	11.25	900	0.1238	0.8559	0.8448	0.8503	0.9822
0.0036	12.5	1000	0.1298	0.8546	0.8362	0.8453	0.9807

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2