bart-large-aeslc-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: 5.5122
• Rouge1: 0.2421
• Rouge2: 0.1162
• Rougel: 0.23
• Rougelsum: 0.2305

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH 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
4.8115	2.5	5	5.6510	0.1512	0.0659	0.1397	0.1397
2.9123	5.0	10	4.9927	0.232	0.1171	0.2223	0.2229
1.4885	7.5	15	5.0836	0.2577	0.1312	0.2487	0.2493
1.2593	10.0	20	5.1864	0.2555	0.1244	0.2435	0.244
0.9244	12.5	25	5.3341	0.2493	0.1196	0.2361	0.2364
0.8451	15.0	30	5.4642	0.2438	0.1175	0.2315	0.2318
0.9148	17.5	35	5.5031	0.2433	0.1167	0.2313	0.2316
0.6394	20.0	40	5.5122	0.2421	0.1162	0.23	0.2305

Framework versions

• Transformers 4.53.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.2