res_nw_irq_aragpt2-large

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

• Loss: 0.1727
• Bleu: 0.0581
• Rouge1: 0.3533
• Rouge2: 0.1255
• Rougel: 0.3493

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: 500
• num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Rouge1	Rouge2	Rougel
0.1933	1.0	2113	0.1727	0.0581	0.3533	0.1255	0.3493
0.0577	2.0	4226	0.1791	0.0870	0.4036	0.1746	0.4004
0.0436	3.0	6339	0.1794	0.0989	0.4264	0.1938	0.4239
0.0328	4.0	8452	0.1930	0.1042	0.4350	0.2026	0.4315
0.0249	5.0	10565	0.2008	0.1122	0.4385	0.2067	0.4361
0.0201	6.0	12678	0.2092	0.1137	0.4386	0.2117	0.4361

Framework versions

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