eslamxm/AraT5-base-title-generation-finetuned-ar-wikilingua

AraT5-base-title-generation-finetuned-ar-xlsum

This model is a fine-tuned version of UBC-NLP/AraT5-base-title-generation on the wiki_lingua dataset. It achieves the following results on the evaluation set:

• Loss: 4.8120
• Rouge-1: 23.29
• Rouge-2: 8.44
• Rouge-l: 20.74
• Gen Len: 18.16
• Bertscore: 70.88

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 250
• num_epochs: 8
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge-1	Rouge-2	Rouge-l	Gen Len	Bertscore
6.1002	1.0	5111	5.2917	18.95	5.84	17.01	17.9	68.69
5.4427	2.0	10222	5.0877	20.61	6.73	18.58	17.14	69.69
5.1876	3.0	15333	4.9631	21.27	7.17	19.09	17.69	69.82
5.0256	4.0	20444	4.8984	21.7	7.53	19.55	17.56	70.18
4.9104	5.0	25555	4.8538	22.23	7.54	19.79	17.6	70.33
4.8251	6.0	30666	4.8309	22.35	7.6	19.96	17.64	70.51
4.7666	7.0	35777	4.8168	22.45	7.81	20.15	17.47	70.61
4.7275	8.0	40888	4.8120	22.67	7.83	20.34	17.56	70.66

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0+cu111
• Datasets 2.1.0
• Tokenizers 0.12.1