flan-t5-rouge-squad-qg

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: 0.3225
• Rouge1: 0.4603
• Rouge2: 0.1838
• Rougel: 0.4115
• Rougelsum: 0.4478

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: 24
• eval_batch_size: 24
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
16.5081	1.0	3	15.3312	0.2528	0.1156	0.2032	0.2053
8.4005	2.0	6	4.6577	0.2538	0.1115	0.1987	0.2066
4.0936	3.0	9	4.0634	0.2540	0.1245	0.2186	0.2184
3.6521	4.0	12	3.6769	0.2898	0.1640	0.2539	0.2607
3.1589	5.0	15	3.1339	0.3017	0.1714	0.2645	0.2717
2.5217	6.0	18	2.3186	0.3017	0.1714	0.2645	0.2717
1.5472	7.0	21	0.9929	0.3164	0.1571	0.2498	0.2563
1.5284	8.0	24	0.6101	0.2596	0.1178	0.2018	0.2043
1.2359	9.0	27	0.4815	0.2596	0.1178	0.2018	0.2043
1.1669	10.0	30	0.3870	0.5138	0.2379	0.4589	0.4960
0.6514	11.0	33	0.3166	0.5138	0.2379	0.4589	0.4960
0.3465	12.0	36	0.2860	0.5138	0.2379	0.4589	0.4960
0.2721	13.0	39	0.2776	0.5138	0.2379	0.4589	0.4960
0.4964	14.0	42	0.2746	0.5152	0.2444	0.4655	0.4940
0.2382	15.0	45	0.2761	0.4675	0.1901	0.4208	0.4483
0.5074	16.0	48	0.2801	0.4675	0.1901	0.4208	0.4483
0.353	17.0	51	0.2858	0.4675	0.1901	0.4208	0.4483
0.1808	18.0	54	0.2916	0.4675	0.1901	0.4208	0.4483
0.2506	19.0	57	0.2961	0.4665	0.1838	0.4145	0.4506
0.2296	20.0	60	0.3027	0.5138	0.2379	0.4589	0.4960
0.3785	21.0	63	0.3073	0.5138	0.2379	0.4589	0.4960
0.2014	22.0	66	0.3107	0.5138	0.2379	0.4589	0.4960
0.4355	23.0	69	0.3131	0.5138	0.2379	0.4589	0.4960
0.1727	24.0	72	0.3159	0.5138	0.2379	0.4589	0.4960
0.1342	25.0	75	0.3173	0.5138	0.2379	0.4589	0.4960
0.193	26.0	78	0.3200	0.5138	0.2379	0.4589	0.4960
0.1703	27.0	81	0.3211	0.5138	0.2379	0.4589	0.4960
0.0676	28.0	84	0.3216	0.4603	0.1838	0.4115	0.4478
0.1207	29.0	87	0.3222	0.4603	0.1838	0.4115	0.4478
0.1002	30.0	90	0.3225	0.4603	0.1838	0.4115	0.4478

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.21.0