bart-base-wsd-finetuned-cve-reason-2

This model is a fine-tuned version of mgkamalesh7/bart-base-wsd-finetuned-cve-reason on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4159
• Rouge1: 91.1806
• Rouge2: 87.5256
• Rougel: 91.1424
• Rougelsum: 91.1124
• Gen Len: 8.6492

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	56	0.4140	89.658	85.4214	89.5042	89.4542	8.7377
No log	2.0	112	0.3450	89.6585	86.3159	89.5529	89.537	8.7344
No log	3.0	168	0.4252	89.2531	85.5599	89.1241	89.1115	8.7311
No log	4.0	224	0.4278	89.4207	85.3854	89.1996	89.2622	8.7443
No log	5.0	280	0.4023	90.0865	86.5253	89.8973	89.9373	8.7475
No log	6.0	336	0.3831	89.6788	86.8093	89.5032	89.5405	8.6557
No log	7.0	392	0.4100	90.7802	87.4674	90.6112	90.6915	8.6721
No log	8.0	448	0.4425	90.4749	87.3615	90.4286	90.3849	8.6459
0.0544	9.0	504	0.4098	90.3948	86.9721	90.4295	90.3163	8.5541
0.0544	10.0	560	0.4289	89.8096	85.6718	89.6744	89.6666	8.6787
0.0544	11.0	616	0.4338	90.9849	87.3715	90.9871	90.9153	8.6787
0.0544	12.0	672	0.4159	91.1806	87.5256	91.1424	91.1124	8.6492

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1