t-5-base-abs2abs

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

• Loss: 1.3203
• Rouge1: 0.6446
• Rouge2: 0.3626
• Rougel: 0.5773
• Rougelsum: 0.5771
• Wer: 0.5292
• Bleurt: -0.1862

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: 2e-05
• train_batch_size: 6
• eval_batch_size: 6
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Wer	Bleurt
No log	0.14	250	1.4708	0.6226	0.3343	0.5514	0.5512	0.559	-0.1681
1.9361	0.27	500	1.4181	0.6277	0.3422	0.5591	0.5588	0.5498	-0.1527
1.9361	0.41	750	1.3918	0.6326	0.3467	0.5633	0.5632	0.5453	-0.1653
1.5072	0.55	1000	1.3740	0.6352	0.3508	0.5664	0.5662	0.541	-0.1653
1.5072	0.68	1250	1.3602	0.6369	0.3528	0.5687	0.5685	0.539	-0.4817
1.4761	0.82	1500	1.3504	0.6388	0.3557	0.5711	0.571	0.5361	-0.1653
1.4761	0.96	1750	1.3424	0.6399	0.3573	0.5728	0.5725	0.5341	-0.1653
1.4475	1.09	2000	1.3368	0.6413	0.3586	0.5737	0.5735	0.5329	-0.4817
1.4475	1.23	2250	1.3324	0.6422	0.36	0.5748	0.5746	0.5316	-0.4726
1.4375	1.36	2500	1.3280	0.6435	0.3608	0.5757	0.5754	0.5309	-0.3069
1.4375	1.5	2750	1.3246	0.644	0.3618	0.5765	0.5763	0.5304	-0.1862
1.4053	1.64	3000	1.3222	0.6443	0.3622	0.5769	0.5767	0.5296	-0.1862
1.4053	1.77	3250	1.3208	0.6446	0.3625	0.5771	0.5769	0.5293	-0.1862
1.3911	1.91	3500	1.3203	0.6446	0.3626	0.5773	0.5771	0.5292	-0.1862

Framework versions

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