res_nw_lev_aragpt2-base

This model is a fine-tuned version of aubmindlab/aragpt2-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0520
• Bleu: 0.1724
• Rouge1: 0.5243
• Rouge2: 0.3044
• Rougel: 0.5218

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
• lr_scheduler_warmup_steps: 500
• num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Rouge1	Rouge2	Rougel
0.26	1.0	5062	0.0696	0.0245	0.3013	0.0862	0.2973
0.0691	2.0	10124	0.0627	0.0520	0.3752	0.1476	0.3720
0.061	3.0	15186	0.0592	0.0728	0.4151	0.1846	0.4119
0.055	4.0	20248	0.0568	0.0853	0.4403	0.2078	0.4371
0.0501	5.0	25310	0.0552	0.1006	0.4609	0.2304	0.4581
0.0458	6.0	30372	0.0542	0.1181	0.4821	0.2520	0.4793
0.0421	7.0	35434	0.0534	0.1341	0.4963	0.2701	0.4938
0.0389	8.0	40496	0.0527	0.1531	0.5119	0.2877	0.5094
0.036	9.0	45558	0.0520	0.1724	0.5243	0.3044	0.5218
0.0335	10.0	50620	0.0522	0.1916	0.5355	0.3184	0.5331
0.0314	11.0	55682	0.0526	0.2161	0.5483	0.3340	0.5464
0.0295	12.0	60744	0.0531	0.2349	0.5567	0.3463	0.5542
0.0278	13.0	65806	0.0534	0.2526	0.5650	0.3578	0.5630
0.0264	14.0	70868	0.0542	0.2696	0.5713	0.3696	0.5696

Framework versions

• Transformers 4.45.0.dev0
• Pytorch 2.3.1+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1