bart-large-cnn-finetuned-roundup-3-8

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

• Loss: 1.4132
• Rouge1: 49.6606
• Rouge2: 28.4044
• Rougel: 31.5419
• Rougelsum: 46.2463
• Gen Len: 142.0

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	258	1.2686	48.8513	28.7007	31.1199	45.7318	142.0
1.1738	2.0	516	1.1884	49.8072	28.9817	31.3611	46.9639	141.6875
1.1738	3.0	774	1.1970	49.3865	28.3426	30.0945	46.4681	141.3438
0.7069	4.0	1032	1.1984	50.6743	29.4728	31.5364	47.989	141.7188
0.7069	5.0	1290	1.2494	49.4461	28.9295	31.0334	46.6611	142.0
0.4618	6.0	1548	1.2954	50.6789	30.2783	32.1932	47.5929	142.0
0.4618	7.0	1806	1.3638	49.9476	30.223	32.4346	46.7383	142.0
0.3293	8.0	2064	1.4132	49.6606	28.4044	31.5419	46.2463	142.0

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1