EN_t5-base_15_spider_nosch_baseline_clean

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

• Loss: 0.3601
• Rouge2 Precision: 0.6091
• Rouge2 Recall: 0.3936
• Rouge2 Fmeasure: 0.4502

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
0.2226	1.0	1083	0.2680	0.5109	0.3348	0.3789
0.1393	2.0	2166	0.2682	0.5693	0.3775	0.4275
0.1034	3.0	3249	0.2706	0.5889	0.3829	0.4354
0.0822	4.0	4332	0.2928	0.5924	0.3855	0.4385
0.0701	5.0	5415	0.2980	0.594	0.3839	0.4381
0.0585	6.0	6498	0.3091	0.6061	0.3946	0.4494
0.0492	7.0	7581	0.3099	0.6254	0.4082	0.4657
0.0446	8.0	8664	0.3189	0.6089	0.3913	0.448
0.0394	9.0	9747	0.3356	0.6028	0.3893	0.445
0.0351	10.0	10830	0.3460	0.6039	0.394	0.4491
0.0331	11.0	11913	0.3455	0.6168	0.3987	0.456
0.0305	12.0	12996	0.3502	0.616	0.3983	0.4557
0.0285	13.0	14079	0.3577	0.6118	0.3949	0.4525
0.028	14.0	15162	0.3582	0.6135	0.3953	0.4522
0.0265	15.0	16245	0.3601	0.6091	0.3936	0.4502

Framework versions

• Transformers 4.26.1
• Pytorch 2.0.1+cu117
• Datasets 2.14.7.dev0
• Tokenizers 0.13.3