flan-t5-large-work-filters

This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0362
Rouge1: 41.8961
Rouge2: 31.4402
Rougel: 41.841
Rougelsum: 41.9024
Gen Len: 18.9259

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: 3e-05
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	Gen Len
0.5256	1.0	213	0.2899	41.8953	29.9382	41.4023	41.4413	18.9788
0.2377	2.0	426	0.1172	42.3662	31.0031	41.997	42.0997	19.0
0.1501	3.0	639	0.1091	42.0009	31.2986	41.8735	41.9067	19.0
0.1256	4.0	852	0.0905	43.6233	32.9567	43.5606	43.6054	18.9788
0.0997	5.0	1065	0.0936	43.4929	32.9118	43.5026	43.5589	18.9577
0.0792	6.0	1278	0.0743	43.3921	32.8388	43.3863	43.4487	18.9577
0.0738	7.0	1491	0.0613	42.3912	31.6893	42.3324	42.375	18.9577
0.0621	8.0	1704	0.0753	42.4408	31.7954	42.391	42.4501	18.9577
0.0664	9.0	1917	0.0568	42.0348	31.4631	41.9591	42.0159	18.9577
0.0575	10.0	2130	0.0576	43.0601	32.8756	42.9724	43.0502	18.9577
0.0488	11.0	2343	0.0473	42.3785	31.845	42.2759	42.37	18.9577
0.0528	12.0	2556	0.0503	43.1495	32.7992	43.1017	43.1919	18.9577
0.0392	13.0	2769	0.0407	42.0459	31.7063	41.9685	42.0368	18.9259
0.0462	14.0	2982	0.0446	43.473	33.1682	43.4607	43.5482	18.9259
0.0449	15.0	3195	0.0426	43.2263	32.5799	43.2171	43.255	18.9577
0.0432	16.0	3408	0.0419	42.2094	31.7081	42.1549	42.2244	18.9577
0.037	17.0	3621	0.0398	42.2089	31.5243	42.1439	42.213	18.9259
0.0376	18.0	3834	0.0402	42.624	31.7967	42.5462	42.6104	18.9259
0.0423	19.0	4047	0.0406	42.6076	31.9496	42.5665	42.6086	18.9259
0.0364	20.0	4260	0.0406	43.4863	33.0331	43.4492	43.5222	18.9259
0.0326	21.0	4473	0.0362	41.8961	31.4402	41.841	41.9024	18.9259
0.0302	22.0	4686	0.0410	42.9891	32.761	42.9509	42.9624	18.9259
0.0318	23.0	4899	0.0411	42.861	32.4727	42.8046	42.8544	18.9259
0.034	24.0	5112	0.0387	42.6177	32.1915	42.4974	42.5653	18.9259
0.0307	25.0	5325	0.0373	43.2371	32.9299	43.2075	43.2857	18.9259
0.0308	26.0	5538	0.0377	42.8476	32.5806	42.7802	42.837	18.9259
0.0282	27.0	5751	0.0381	42.9285	32.4737	42.8965	42.945	18.9259
0.0277	28.0	5964	0.0383	42.6384	31.6781	42.567	42.6305	18.9259
0.0316	29.0	6177	0.0380	42.9983	32.5656	42.9407	42.9974	18.9259
0.0357	30.0	6390	0.0378	43.0447	32.5656	43.0102	43.0802	18.9259

Framework versions

Transformers 4.27.2
Pytorch 2.0.0+cu118
Datasets 2.9.0
Tokenizers 0.13.3

madhav-devrev/flan-t5-large-work-filters

flan-t5-large-work-filters

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

为此模型做种