EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-09-26_ent_gates_exitloss

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: 1.1687
• Accuracy: 0.695
• Exit 0 Accuracy: 0.11
• Exit 1 Accuracy: 0.11
• Exit 2 Accuracy: 0.3625
• Exit 3 Accuracy: 0.6375
• Exit 4 Accuracy: 0.69

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: 16
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 12
• total_train_batch_size: 192
• 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	4	2.7393	0.1175	0.06	0.0925	0.085	0.0625	0.0625
No log	1.96	8	2.6761	0.1625	0.07	0.0925	0.085	0.0625	0.0625
No log	2.96	12	2.6336	0.1825	0.0775	0.1	0.09	0.0625	0.0625
No log	3.96	16	2.6046	0.21	0.065	0.105	0.0775	0.0625	0.0625
No log	4.96	20	2.6355	0.17	0.0675	0.105	0.06	0.115	0.0875
No log	5.96	24	2.5487	0.1925	0.0725	0.1075	0.09	0.13	0.1075
No log	6.96	28	2.4605	0.275	0.0875	0.1075	0.0925	0.1675	0.13
No log	7.96	32	2.3986	0.2475	0.09	0.1125	0.0925	0.22	0.215
No log	8.96	36	2.3182	0.3	0.1	0.1125	0.1075	0.2475	0.29
No log	9.96	40	2.2072	0.35	0.1025	0.1125	0.1175	0.295	0.36
No log	10.96	44	2.1187	0.425	0.1025	0.1125	0.1275	0.3175	0.4025
No log	11.96	48	2.0086	0.455	0.0975	0.11	0.16	0.3675	0.4475
No log	12.96	52	1.9037	0.4775	0.095	0.11	0.1725	0.4025	0.465
No log	13.96	56	1.8088	0.515	0.0925	0.11	0.1875	0.4425	0.49
No log	14.96	60	1.7198	0.5475	0.095	0.1075	0.2125	0.475	0.525
No log	15.96	64	1.6502	0.5825	0.095	0.105	0.225	0.4825	0.5425
No log	16.96	68	1.5650	0.58	0.0975	0.12	0.235	0.5175	0.5625
No log	17.96	72	1.4998	0.6025	0.1025	0.1125	0.2475	0.5375	0.565
No log	18.96	76	1.4608	0.6025	0.1075	0.11	0.275	0.5375	0.6025
No log	19.96	80	1.3988	0.62	0.1075	0.11	0.285	0.545	0.6025
No log	20.96	84	1.3833	0.6275	0.1075	0.11	0.2825	0.555	0.61
No log	21.96	88	1.3400	0.6475	0.11	0.11	0.2875	0.57	0.62
No log	22.96	92	1.3355	0.6425	0.1125	0.11	0.29	0.575	0.6375
No log	23.96	96	1.2812	0.6525	0.11	0.11	0.295	0.585	0.635
No log	24.96	100	1.2769	0.6425	0.11	0.11	0.31	0.585	0.6275
No log	25.96	104	1.2410	0.665	0.11	0.1075	0.315	0.59	0.6375
No log	26.96	108	1.2272	0.6725	0.1075	0.1075	0.32	0.595	0.64
No log	27.96	112	1.2168	0.67	0.11	0.1075	0.3225	0.595	0.645
No log	28.96	116	1.1919	0.675	0.11	0.1075	0.3325	0.595	0.64
No log	29.96	120	1.1948	0.6825	0.11	0.1075	0.3375	0.6	0.655
No log	30.96	124	1.1802	0.6875	0.1075	0.1075	0.3325	0.605	0.665
No log	31.96	128	1.1939	0.68	0.11	0.1075	0.345	0.615	0.65
No log	32.96	132	1.1690	0.6925	0.1075	0.1075	0.34	0.615	0.665
No log	33.96	136	1.1763	0.68	0.105	0.1075	0.3475	0.6175	0.6525
No log	34.96	140	1.1851	0.6875	0.105	0.1075	0.3525	0.615	0.6675
No log	35.96	144	1.1574	0.6925	0.11	0.1075	0.355	0.62	0.6675
No log	36.96	148	1.1618	0.68	0.1075	0.1075	0.36	0.62	0.665
No log	37.96	152	1.1731	0.6825	0.105	0.1075	0.35	0.615	0.6575
No log	38.96	156	1.1550	0.68	0.1075	0.1075	0.3425	0.6225	0.665
No log	39.96	160	1.1553	0.7	0.11	0.1075	0.3475	0.625	0.675
No log	40.96	164	1.1708	0.6875	0.1125	0.1075	0.355	0.6275	0.665
No log	41.96	168	1.1366	0.7	0.115	0.1075	0.3525	0.63	0.68
No log	42.96	172	1.1699	0.69	0.115	0.1075	0.3575	0.63	0.6825
No log	43.96	176	1.1548	0.7025	0.1125	0.1075	0.3525	0.6325	0.6725
No log	44.96	180	1.1628	0.6925	0.11	0.1075	0.3575	0.635	0.675
No log	45.96	184	1.1620	0.695	0.11	0.1075	0.355	0.6325	0.6875
No log	46.96	188	1.1668	0.695	0.1125	0.1075	0.3525	0.645	0.68
No log	47.96	192	1.1595	0.6975	0.11	0.1075	0.3475	0.635	0.6875
No log	48.96	196	1.1622	0.7025	0.11	0.1075	0.355	0.63	0.68
No log	49.96	200	1.1779	0.695	0.1075	0.1075	0.3575	0.635	0.685
No log	50.96	204	1.1656	0.695	0.11	0.1075	0.3525	0.635	0.685
No log	51.96	208	1.1536	0.705	0.1075	0.1075	0.355	0.635	0.69
No log	52.96	212	1.1675	0.7025	0.1075	0.11	0.355	0.635	0.6975
No log	53.96	216	1.1775	0.6925	0.1075	0.11	0.3575	0.6325	0.6925
No log	54.96	220	1.1690	0.7	0.1075	0.11	0.36	0.6375	0.685
No log	55.96	224	1.1700	0.7	0.11	0.11	0.3625	0.64	0.69
No log	56.96	228	1.1637	0.7025	0.11	0.11	0.3625	0.64	0.6875
No log	57.96	232	1.1640	0.695	0.11	0.11	0.3625	0.6375	0.6875
No log	58.96	236	1.1663	0.6975	0.11	0.11	0.3625	0.6375	0.6875
No log	59.96	240	1.1687	0.695	0.11	0.11	0.3625	0.6375	0.69

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1.post200
• Datasets 2.9.0
• Tokenizers 0.13.2