learning_rate: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Json Validity	Field Match Avg
1.6843	0.04	4	1.6791	0.0	0.0
1.2435	0.08	8	1.1588	0.0	0.0
0.9726	0.12	12	0.8497	0.0	0.0
0.3672	0.16	16	0.6707	0.0	0.0
0.8473	0.2	20	0.5506	0.0	0.0
0.3753	0.24	24	0.4935	0.0	0.0
0.5084	0.28	28	0.4973	0.0	0.0
0.3072	0.32	32	0.4974	0.0	0.0
0.2135	0.36	36	0.4716	0.0	0.0
0.3368	0.4	40	0.4641	0.0	0.0
0.4291	0.44	44	0.4585	0.0	0.0
0.334	0.48	48	0.4150	0.0	0.0
0.2791	0.52	52	0.4408	0.0	0.0
0.287	0.56	56	0.4097	0.0	0.0
0.2269	0.6	60	0.3962	0.0	0.0
0.3634	0.64	64	0.3881	0.0	0.0
0.352	0.68	68	0.3956	0.0	0.0
0.2697	0.72	72	0.3953	0.0	0.0
0.3239	0.76	76	0.3821	0.0	0.0
0.2503	0.8	80	0.3809	0.0	0.0
0.278	0.84	84	0.3980	0.2	1.0
0.2364	0.88	88	0.4126	0.0	0.0
0.1774	0.92	92	0.4199	0.0	0.0
0.5384	0.96	96	0.4227	0.0	0.0
0.21	1.0	100	0.4168	0.0	0.0
0.2008	1.04	104	0.3820	0.0	0.0
0.0569	1.08	108	0.3619	0.0	0.0
0.1999	1.12	112	0.3687	0.0	0.0
0.1869	1.16	116	0.3742	0.0	0.0
0.2146	1.2	120	0.3774	0.0	0.0
0.2165	1.24	124	0.3805	0.0	0.0
0.1742	1.28	128	0.3623	0.0	0.0
0.392	1.32	132	0.3592	0.0	0.0
0.2822	1.3600	136	0.3600	0.0	0.0
0.1651	1.4	140	0.3579	0.0	0.0
0.259	1.44	144	0.3640	0.0	0.0
0.2883	1.48	148	0.3653	0.0	0.0
0.0865	1.52	152	0.3669	0.0	0.0
0.1842	1.56	156	0.3732	0.0	0.0
0.1547	1.6	160	0.3852	0.0	0.0
0.1551	1.6400	164	0.3732	0.0	0.0
0.0667	1.6800	168	0.3655	0.0	0.0
0.0763	1.72	172	0.3654	0.0	0.0
0.1045	1.76	176	0.3698	0.0	0.0
0.1016	1.8	180	0.3681	0.0	0.0
0.1273	1.8400	184	0.3711	0.0	0.0
0.0772	1.88	188	0.3717	0.0	0.0
0.123	1.92	192	0.3775	0.0	0.0
0.1533	1.96	196	0.3606	0.0	0.0
0.0748	2.0	200	0.3529	0.0	0.0
0.1028	2.04	204	0.3554	0.0	0.0
0.0557	2.08	208	0.3690	0.0	0.0
0.134	2.12	212	0.3848	0.0	0.0
0.0785	2.16	216	0.3964	0.0	0.0
0.0602	2.2	220	0.4010	0.0	0.0
0.0426	2.24	224	0.4038	0.0	0.0
0.0211	2.2800	228	0.4033	0.0	0.0
0.0632	2.32	232	0.4067	0.0	0.0
0.1438	2.36	236	0.4087	0.0	0.0
0.0917	2.4	240	0.4094	0.0	0.0
0.0292	2.44	244	0.4128	0.0	0.0
0.0339	2.48	248	0.4189	0.0	0.0
0.0619	2.52	252	0.4250	0.0	0.0
0.0252	2.56	256	0.4229	0.0	0.0
0.1563	2.6	260	0.4226	0.0	0.0
0.0258	2.64	264	0.4277	0.0	0.0
0.1214	2.68	268	0.4225	0.0	0.0
0.0562	2.7200	272	0.4237	0.0	0.0
0.1413	2.76	276	0.4195	0.0	0.0
0.0922	2.8	280	0.4172	0.0	0.0
0.0061	2.84	284	0.4155	0.0	0.0
0.0863	2.88	288	0.4220	0.0	0.0
0.059	2.92	292	0.4154	0.0	0.0
0.0188	2.96	296	0.4162	0.0	0.0
0.2014	3.0	300	0.4194	0.0	0.0

Framework versions

PEFT 0.15.2
Transformers 4.47.1
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.1

veronikayu/paligemma-imgtojson

paligemma-imgtojson

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

veronikayu/
paligemma-imgtojson