bart-large-finetuned-xsum – AI Model by aristotletan | AlphaNeural AI

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bart-large-finetuned-xsum

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bart-large-finetuned-xsum

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

Loss: 0.8497
Rouge1: 15.3934
Rouge2: 7.0378
Rougel: 13.9522
Rougelsum: 14.3541
Gen Len: 20.0

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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.0964	1.0	1735	0.9365	18.703	12.7539	18.1293	18.5397	20.0
0.95	2.0	3470	0.8871	19.5223	13.0938	18.9148	18.8363	20.0
0.8687	3.0	5205	0.8587	15.0915	7.142	13.6693	14.5975	20.0
0.7989	4.0	6940	0.8569	18.243	11.4495	17.4326	17.489	20.0
0.7493	5.0	8675	0.8497	15.3934	7.0378	13.9522	14.3541	20.0

Framework versions

Transformers 4.8.2
Pytorch 1.9.0+cu102
Datasets 1.10.0
Tokenizers 0.10.3