bart-large-cnn-finetuned-roundup-4

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: 1.2573
• Rouge1: 49.0193
• Rouge2: 28.6311
• Rougel: 31.3363
• Rougelsum: 46.1408
• 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: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	132	1.3178	48.4526	28.6361	30.2875	45.4822	142.0
No log	2.0	264	1.2404	48.139	28.2459	29.3584	45.0785	142.0
No log	3.0	396	1.2389	49.74	29.7834	33.143	46.8147	142.0
0.9855	4.0	528	1.2573	49.0193	28.6311	31.3363	46.1408	142.0

Framework versions

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