t5-flan-semantic

This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0553
• Rouge1: 0.8952
• Rouge2: 0.8673
• Rougel: 0.8952
• Rougelsum: 0.8952

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.0194	1.0	2	0.0082	0.9333	0.9158	0.9333	0.9333
0.0042	2.0	4	0.0408	0.9238	0.9031	0.9238	0.9238
0.0002	3.0	6	0.0647	0.9238	0.9031	0.9238	0.9238
0.0002	4.0	8	0.1117	0.9238	0.9031	0.9238	0.9238
0.0007	5.0	10	0.1404	0.9238	0.9031	0.9238	0.9238
0.0006	6.0	12	0.0987	0.9238	0.9031	0.9238	0.9238
0.0005	7.0	14	0.0587	0.9238	0.9031	0.9238	0.9238
0.0005	8.0	16	0.0251	0.9238	0.9031	0.9238	0.9238
0.0022	9.0	18	0.0128	0.9095	0.8852	0.9095	0.9095
0.0002	10.0	20	0.0228	0.8952	0.8622	0.8952	0.8952
0.0003	11.0	22	0.0351	0.8952	0.8622	0.8952	0.8952
0.0008	12.0	24	0.0374	0.9190	0.8980	0.9190	0.9190
0.0004	13.0	26	0.0462	0.8952	0.8673	0.8952	0.8952
0.0	14.0	28	0.0610	0.8952	0.8673	0.8952	0.8952
0.0001	15.0	30	0.0737	0.8952	0.8673	0.8952	0.8952
0.0005	16.0	32	0.0839	0.8952	0.8673	0.8952	0.8952
0.0002	17.0	34	0.0917	0.8952	0.8673	0.8952	0.8952
0.0009	18.0	36	0.1001	0.8952	0.8673	0.8952	0.8952
0.0005	19.0	38	0.1054	0.8952	0.8673	0.8952	0.8952
0.0012	20.0	40	0.1079	0.8952	0.8673	0.8952	0.8952
0.0	21.0	42	0.1085	0.8952	0.8673	0.8952	0.8952
0.0	22.0	44	0.1015	0.8952	0.8673	0.8952	0.8952
0.0018	23.0	46	0.0862	0.8952	0.8673	0.8952	0.8952
0.0001	24.0	48	0.0752	0.8952	0.8673	0.8952	0.8952
0.0004	25.0	50	0.0675	0.8952	0.8673	0.8952	0.8952
0.0001	26.0	52	0.0623	0.8952	0.8673	0.8952	0.8952
0.0	27.0	54	0.0589	0.8952	0.8673	0.8952	0.8952
0.0005	28.0	56	0.0568	0.8952	0.8673	0.8952	0.8952
0.0002	29.0	58	0.0557	0.8952	0.8673	0.8952	0.8952
0.0002	30.0	60	0.0553	0.8952	0.8673	0.8952	0.8952

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2