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: test
    results: []

test

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: 0.2763
Precision: 0.5109
Recall: 0.6026
F1: 0.5529
Accuracy: 0.9222

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	0.6800	0.3371	0.3846	0.3593	0.7682
No log	16.67	200	0.3088	0.5204	0.6538	0.5795	0.9156
No log	25.0	300	0.2142	0.5326	0.6282	0.5765	0.9305
No log	33.33	400	0.2301	0.5795	0.6538	0.6145	0.9288
0.4115	41.67	500	0.2426	0.5618	0.6410	0.5988	0.9272
0.4115	50.0	600	0.4171	0.6190	0.6667	0.6420	0.8924
0.4115	58.33	700	0.2265	0.5393	0.6154	0.5749	0.9371
0.4115	66.67	800	0.2869	0.5506	0.6282	0.5868	0.9156
0.4115	75.0	900	0.2633	0.5568	0.6282	0.5904	0.9272
0.0231	83.33	1000	0.2763	0.5109	0.6026	0.5529	0.9222

Framework versions

Transformers 4.33.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3