reciept-model-2500

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

• Loss: 0.0043
• Precision: 0.9673
• Recall: 0.9625
• F1: 0.9649
• Accuracy: 0.9993

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: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.62	100	0.0150	0.8575	0.8725	0.8649	0.9972
No log	1.25	200	0.0075	0.8756	0.9325	0.9031	0.9979
No log	1.88	300	0.0154	0.8744	0.8875	0.8809	0.9973
No log	2.5	400	0.0118	0.8881	0.9525	0.9192	0.9982
0.0029	3.12	500	0.0091	0.9158	0.925	0.9204	0.9983
0.0029	3.75	600	0.0167	0.8720	0.9025	0.8870	0.9975
0.0029	4.38	700	0.0092	0.9183	0.9275	0.9229	0.9983
0.0029	5.0	800	0.0113	0.8843	0.9175	0.9006	0.9979
0.0029	5.62	900	0.0106	0.9349	0.8975	0.9158	0.9982
0.0017	6.25	1000	0.0043	0.9673	0.9625	0.9649	0.9993
0.0017	6.88	1100	0.0044	0.9602	0.965	0.9626	0.9993
0.0017	7.5	1200	0.0118	0.9246	0.92	0.9223	0.9982
0.0017	8.12	1300	0.0067	0.9406	0.95	0.9453	0.9988
0.0017	8.75	1400	0.0083	0.9409	0.955	0.9479	0.9989
0.001	9.38	1500	0.0060	0.9495	0.94	0.9447	0.9988
0.001	10.0	1600	0.0078	0.9369	0.9275	0.9322	0.9985
0.001	10.62	1700	0.0093	0.9248	0.9525	0.9384	0.9986
0.001	11.25	1800	0.0097	0.9062	0.9425	0.9240	0.9983
0.001	11.88	1900	0.0100	0.9098	0.9325	0.9210	0.9982
0.0006	12.5	2000	0.0111	0.9113	0.925	0.9181	0.9981
0.0006	13.12	2100	0.0107	0.9275	0.9275	0.9275	0.9983
0.0006	13.75	2200	0.0105	0.9279	0.9325	0.9302	0.9984
0.0006	14.38	2300	0.0109	0.9325	0.9325	0.9325	0.9985
0.0006	15.0	2400	0.0109	0.9325	0.9325	0.9325	0.9985
0.0003	15.62	2500	0.0109	0.9325	0.9325	0.9325	0.9985

Framework versions

• Transformers 4.38.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1