longt5_xl_sfd_bp_20

This model is a fine-tuned version of google/long-t5-tglobal-xl on the learn3r/summ_screen_fd_bp dataset. It achieves the following results on the evaluation set:

• Loss: 1.5032
• Rouge1: 22.11
• Rouge2: 7.544
• Rougel: 19.7035
• Rougelsum: 20.2813
• Gen Len: 497.8783

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: 0.001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.3973	0.97	14	1.9074	10.6164	2.4585	10.4856	9.8193	511.0
1.9188	1.95	28	1.7082	17.4258	4.2128	16.5213	15.8377	511.0
1.4297	2.99	43	1.5073	18.6504	5.4242	17.2648	17.0203	506.7745
1.2759	3.97	57	1.5032	22.11	7.544	19.7035	20.2813	497.8783
1.1421	4.94	71	1.5462	20.6049	6.7146	18.5084	19.0876	503.6024
0.9605	5.98	86	1.6233	22.6777	7.9362	18.7936	21.41	510.2730
0.8082	6.96	100	1.7575	26.5338	9.9474	20.3789	25.0767	511.0
0.664	8.0	115	1.7702	35.1918	13.7223	26.1763	33.3997	329.7151
0.5471	8.97	129	1.9383	27.0414	10.4166	20.1803	25.6283	506.8279
0.4349	9.95	143	1.9608	29.5613	11.7633	22.7176	27.9563	454.7033
0.4338	10.99	158	2.1197	31.2004	12.8569	22.1282	29.8827	493.3234
0.2887	11.97	172	2.1205	34.9566	13.8574	25.1764	33.2914	381.3591
0.2753	12.94	186	2.4299	36.3877	13.8584	25.7829	34.8601	338.7240
0.2114	13.98	201	2.5799	39.7535	16.1209	27.8512	37.8553	302.4837
0.1805	14.96	215	2.6123	33.3254	13.0868	23.3214	31.7901	442.9258
0.1543	16.0	230	2.5635	31.7816	13.1085	22.9117	30.2286	463.0801
0.5166	16.97	244	2.5134	30.3969	12.1295	21.6616	28.7606	511.0
0.1117	17.95	258	2.8109	35.336	14.9492	24.1938	33.822	431.1157
0.0895	18.99	273	2.7577	41.0982	16.3935	28.1073	39.1641	240.1365
0.0779	19.48	280	2.8927	32.7788	13.9352	22.5175	31.548	488.5134

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu121
• Datasets 2.14.5
• Tokenizers 0.14.1