antonkurylo/t5-base-news_headlines_8tokens

t5-base-news_headlines

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

• Loss: 0.8974
• Rouge1: 57.2262
• Rouge2: 42.0378
• Rougel: 56.5748
• Rougelsum: 56.5201

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.977	1.0	1531	1.3885	41.7045	23.3673	40.7292	40.6837
1.4827	2.0	3062	1.2265	46.2602	27.7036	45.3412	45.3728
1.2617	3.0	4593	1.0713	49.6738	32.0177	48.9186	48.9156
1.1168	4.0	6124	0.9923	52.3824	35.7493	51.7434	51.706
1.0041	5.0	7655	0.9439	55.6842	40.0864	54.9503	55.0016
0.9305	6.0	9186	0.9085	56.5987	41.4443	55.9192	55.9222
0.8763	7.0	10717	0.8974	57.2262	42.0378	56.5748	56.5201

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3