EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-10-29_two_text_visual

This model is a fine-tuned version of jordyvl/LayoutLMv3_RVL-CDIP_NK100 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0358
• Accuracy: 0.795
• Exit 0 Accuracy: 0.1925
• Exit 1 Accuracy: 0.0725
• Exit 2 Accuracy: 0.0625
• Exit 3 Accuracy: 0.0875
• Exit 4 Accuracy: 0.775

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: 1
• seed: 42
• gradient_accumulation_steps: 24
• total_train_batch_size: 48
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 60

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Exit 0 Accuracy	Exit 1 Accuracy	Exit 2 Accuracy	Exit 3 Accuracy	Exit 4 Accuracy
No log	0.96	16	0.9549	0.7975	0.07	0.0625	0.0625	0.0775	0.3425
No log	1.98	33	0.9581	0.7975	0.0725	0.0625	0.0625	0.0625	0.3475
No log	3.0	50	0.9613	0.7975	0.09	0.0625	0.0625	0.0625	0.395
No log	3.96	66	0.9641	0.7975	0.09	0.0625	0.0625	0.08	0.44
No log	4.98	83	0.9669	0.7975	0.0925	0.0625	0.0625	0.0625	0.45
No log	6.0	100	0.9694	0.7975	0.1	0.0625	0.0625	0.0625	0.495
No log	6.96	116	0.9716	0.7975	0.0975	0.0625	0.0625	0.0625	0.51
No log	7.98	133	0.9741	0.7975	0.0975	0.0625	0.0625	0.0625	0.515
No log	9.0	150	0.9767	0.7975	0.1	0.0625	0.0625	0.0625	0.53
No log	9.96	166	0.9789	0.7975	0.1025	0.0625	0.0625	0.0625	0.575
No log	10.98	183	0.9815	0.7975	0.1125	0.0625	0.0625	0.0625	0.5825
No log	12.0	200	0.9843	0.7975	0.12	0.0625	0.0625	0.0625	0.6175
No log	12.96	216	0.9865	0.7975	0.1225	0.0625	0.0625	0.0625	0.635
No log	13.98	233	0.9887	0.7975	0.12	0.0625	0.0625	0.0625	0.66
No log	15.0	250	0.9909	0.7975	0.1225	0.0625	0.0625	0.0625	0.6775
No log	15.96	266	0.9933	0.7975	0.135	0.0625	0.0625	0.0625	0.6925
No log	16.98	283	0.9955	0.7975	0.14	0.0625	0.0625	0.0625	0.7125
No log	18.0	300	0.9979	0.7975	0.135	0.0625	0.0625	0.1	0.7075
No log	18.96	316	0.9999	0.7975	0.1275	0.0625	0.0625	0.1	0.7075
No log	19.98	333	1.0017	0.7975	0.1275	0.0625	0.0625	0.0675	0.7225
No log	21.0	350	1.0033	0.7975	0.125	0.0625	0.0625	0.0625	0.735
No log	21.96	366	1.0047	0.7975	0.1275	0.0625	0.0625	0.0625	0.765
No log	22.98	383	1.0065	0.7975	0.1325	0.0625	0.0625	0.0625	0.76
No log	24.0	400	1.0082	0.7975	0.1275	0.095	0.065	0.0625	0.7675
No log	24.96	416	1.0099	0.7975	0.1325	0.06	0.1	0.0625	0.78
No log	25.98	433	1.0114	0.7975	0.13	0.06	0.0975	0.0625	0.7825
No log	27.0	450	1.0129	0.7975	0.13	0.0725	0.09	0.0625	0.79
No log	27.96	466	1.0143	0.795	0.135	0.105	0.0625	0.0625	0.7825
No log	28.98	483	1.0158	0.795	0.14	0.095	0.0625	0.0625	0.775
2.5042	30.0	500	1.0174	0.795	0.15	0.115	0.0625	0.0625	0.7775
2.5042	30.96	516	1.0187	0.795	0.1425	0.095	0.0625	0.0625	0.7775
2.5042	31.98	533	1.0200	0.795	0.1425	0.1175	0.0625	0.0625	0.7775
2.5042	33.0	550	1.0214	0.795	0.1525	0.09	0.0625	0.0625	0.7725
2.5042	33.96	566	1.0227	0.795	0.1675	0.08	0.0625	0.0625	0.77
2.5042	34.98	583	1.0238	0.795	0.175	0.085	0.0625	0.085	0.77
2.5042	36.0	600	1.0248	0.795	0.1775	0.0775	0.0625	0.105	0.7725
2.5042	36.96	616	1.0259	0.795	0.1825	0.085	0.0625	0.105	0.7675
2.5042	37.98	633	1.0270	0.795	0.1975	0.08	0.0625	0.125	0.76
2.5042	39.0	650	1.0278	0.795	0.2	0.08	0.0625	0.11	0.765
2.5042	39.96	666	1.0285	0.795	0.1875	0.07	0.0625	0.11	0.7625
2.5042	40.98	683	1.0292	0.795	0.18	0.07	0.0625	0.115	0.7625
2.5042	42.0	700	1.0301	0.795	0.1875	0.065	0.0625	0.115	0.7625
2.5042	42.96	716	1.0308	0.795	0.19	0.0625	0.0625	0.115	0.76
2.5042	43.98	733	1.0314	0.795	0.1975	0.0625	0.0625	0.1075	0.7625
2.5042	45.0	750	1.0320	0.795	0.2	0.0625	0.0625	0.1075	0.7675
2.5042	45.96	766	1.0325	0.795	0.2025	0.065	0.0625	0.1075	0.7675
2.5042	46.98	783	1.0331	0.795	0.205	0.075	0.0625	0.105	0.7675
2.5042	48.0	800	1.0336	0.795	0.2	0.075	0.0625	0.1025	0.77
2.5042	48.96	816	1.0341	0.795	0.2025	0.08	0.0625	0.1025	0.775
2.5042	49.98	833	1.0345	0.795	0.1825	0.0825	0.0625	0.0975	0.775
2.5042	51.0	850	1.0348	0.795	0.1825	0.0825	0.0625	0.1	0.775
2.5042	51.96	866	1.0351	0.795	0.1825	0.0775	0.0625	0.105	0.775
2.5042	52.98	883	1.0353	0.795	0.185	0.0775	0.0625	0.0975	0.775
2.5042	54.0	900	1.0355	0.795	0.1875	0.0825	0.0625	0.09	0.775
2.5042	54.96	916	1.0357	0.795	0.195	0.0775	0.0625	0.0875	0.775
2.5042	55.98	933	1.0357	0.795	0.1925	0.0725	0.0625	0.09	0.775
2.5042	57.0	950	1.0358	0.795	0.1925	0.0725	0.0625	0.09	0.775
2.5042	57.6	960	1.0358	0.795	0.1925	0.0725	0.0625	0.0875	0.775

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3