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-finetuned-cord_100
    results: []

layoutlmv3-finetuned-cord_100

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: 0.3036
Precision: 0.9149
Recall: 0.9309
F1: 0.9228
Accuracy: 0.9419

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: 5
eval_batch_size: 5
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	4.17	250	0.6391	0.8080	0.8093	0.8087	0.8312
0.9327	8.33	500	0.3636	0.8790	0.8891	0.8840	0.9088
0.9327	12.5	750	0.3144	0.9001	0.9103	0.9052	0.9288
0.1743	16.67	1000	0.2957	0.9102	0.9240	0.9170	0.9360
0.1743	20.83	1250	0.2963	0.9109	0.9248	0.9178	0.9334
0.0551	25.0	1500	0.2943	0.9207	0.9263	0.9235	0.9411
0.0551	29.17	1750	0.3034	0.9145	0.9263	0.9203	0.9360
0.0249	33.33	2000	0.3059	0.9162	0.9301	0.9231	0.9394
0.0249	37.5	2250	0.3019	0.9147	0.9293	0.9220	0.9385
0.0153	41.67	2500	0.3036	0.9149	0.9309	0.9228	0.9419

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0