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

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

• Loss: 3.5633
• Rouge1: 0.1587
• Rouge2: 0.0334
• Rougel: 0.129
• Rougelsum: 0.1288

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 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
4.7322	1.6667	5	4.2561	0.1179	0.0141	0.0951	0.0949
3.9516	3.3333	10	3.7572	0.1227	0.0154	0.0987	0.0986
3.2504	5.0	15	3.5486	0.1349	0.0196	0.1082	0.1081
2.8546	6.6667	20	3.4719	0.1518	0.0271	0.1219	0.1217
2.6338	8.3333	25	3.4529	0.1559	0.03	0.1253	0.1251
2.3835	10.0	30	3.4654	0.1518	0.0303	0.124	0.124
2.1009	11.6667	35	3.4887	0.1486	0.0307	0.1215	0.1213
2.0342	13.3333	40	3.5124	0.154	0.0316	0.1263	0.1259
1.7477	15.0	45	3.5348	0.1541	0.031	0.1258	0.1256
1.8574	16.6667	50	3.5515	0.1566	0.0324	0.128	0.1277
1.7186	18.3333	55	3.5593	0.159	0.0331	0.1292	0.129
1.5622	20.0	60	3.5633	0.1587	0.0334	0.129	0.1288

Framework versions

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