layoutlmv2-large-uncased-finetuned-vi-infovqa

This model is a fine-tuned version of microsoft/layoutlmv2-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 8.5806

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 250500
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.17	100	4.6181
No log	0.33	200	4.3357
No log	0.5	300	4.3897
No log	0.66	400	4.8238
4.4277	0.83	500	3.9088
4.4277	0.99	600	3.6063
4.4277	1.16	700	3.4278
4.4277	1.32	800	3.5428
4.4277	1.49	900	3.4331
3.0413	1.65	1000	3.3699
3.0413	1.82	1100	3.3622
3.0413	1.98	1200	3.5294
3.0413	2.15	1300	3.7918
3.0413	2.31	1400	3.4007
2.0843	2.48	1500	4.0296
2.0843	2.64	1600	4.1852
2.0843	2.81	1700	3.6690
2.0843	2.97	1800	3.6089
2.0843	3.14	1900	5.5534
1.7527	3.3	2000	4.7498
1.7527	3.47	2100	5.2691
1.7527	3.63	2200	5.1324
1.7527	3.8	2300	4.5912
1.7527	3.96	2400	4.1727
1.2037	4.13	2500	6.1174
1.2037	4.29	2600	5.7172
1.2037	4.46	2700	5.8843
1.2037	4.62	2800	6.4232
1.2037	4.79	2900	7.4486
0.8386	4.95	3000	7.1946
0.8386	5.12	3100	7.9869
0.8386	5.28	3200	8.0310
0.8386	5.45	3300	8.2954
0.8386	5.61	3400	8.5361
0.4389	5.78	3500	8.6040
0.4389	5.94	3600	8.5806

Framework versions

• Transformers 4.15.0
• Pytorch 1.8.0+cu101
• Datasets 1.17.0
• Tokenizers 0.10.3