bart-large-reddit_tifu-sentence-paraphrased-10-cnt-supervised-basic

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

• Loss: 3.4826
• Rouge1: 0.2091
• Rouge2: 0.0508
• Rougel: 0.1637
• Rougelsum: 0.1634

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: 1e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
4.0417	1.6667	5	3.6114	0.1191	0.0147	0.0957	0.0958
3.079	3.3333	10	3.2036	0.1358	0.0211	0.1084	0.1083
2.1736	5.0	15	3.0838	0.1593	0.0327	0.1272	0.1271
1.8915	6.6667	20	3.0977	0.1792	0.0387	0.1425	0.1422
1.4258	8.3333	25	3.1460	0.1862	0.0404	0.1461	0.146
1.2427	10.0	30	3.1861	0.194	0.0448	0.1528	0.1527
0.9539	11.6667	35	3.2429	0.1962	0.0456	0.1545	0.1542
0.8726	13.3333	40	3.3101	0.2001	0.0479	0.1572	0.1571
0.6842	15.0	45	3.3727	0.2045	0.0493	0.1597	0.1594
0.5764	16.6667	50	3.4268	0.2062	0.0503	0.1608	0.1606
0.7363	18.3333	55	3.4660	0.2084	0.0504	0.1631	0.1629
0.4627	20.0	60	3.4826	0.2091	0.0508	0.1637	0.1634

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.1+cu128
• Datasets 3.6.0
• Tokenizers 0.22.1