bart-base-xsum

Training: The model has been trained using the script provided in the following repository https://github.com/MorenoLaQuatra/transformers-tasks-templates

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

• Loss: 0.8051
• R1: 0.5643
• R2: 0.3017
• Rl: 0.5427
• Rlsum: 0.5427

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: 32
• eval_batch_size: 32
• 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	R1	R2	Rl	Rlsum
0.8983	1.0	6377	0.8145	0.5443	0.2724	0.5212	0.5211
0.8211	2.0	12754	0.7940	0.5519	0.2831	0.5295	0.5295
0.7701	3.0	19131	0.7839	0.5569	0.2896	0.5347	0.5348
0.7046	4.0	25508	0.7792	0.5615	0.2956	0.5394	0.5393
0.6837	5.0	31885	0.7806	0.5631	0.2993	0.5416	0.5416
0.6412	6.0	38262	0.7816	0.5643	0.301	0.5427	0.5426
0.6113	7.0	44639	0.7881	0.5645	0.3017	0.5428	0.5428
0.5855	8.0	51016	0.7921	0.5651	0.303	0.5433	0.5432
0.5636	9.0	57393	0.7972	0.5649	0.3032	0.5433	0.5433
0.5482	10.0	63770	0.7996	0.565	0.3036	0.5436	0.5435

Framework versions

• Transformers 4.22.1
• Pytorch 1.11.0+cu113
• Datasets 2.0.0
• Tokenizers 0.11.6