bart-dnc-booksum – AI Model by UNIST-Eunchan | AlphaNeural AI

You can deploy this model and start earning money today!

UNIST-Eunchan/
bart-dnc-booksum

like

0

text2text-generation

generated_from_trainer

endpoints_compatible

Views

No views yet

bart-dnc-booksum

This model is a fine-tuned version of facebook/bart-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 6.5809

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 40
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.7554	0.16	150	4.3521
0.3115	0.32	300	4.9631
0.3536	0.48	450	4.8518
0.3419	0.64	600	4.8791
0.2082	0.8	750	5.8989
0.3123	0.97	900	4.8499
0.1517	1.13	1050	5.3516
0.2184	1.29	1200	5.5229
0.217	1.45	1350	5.7270
0.1375	1.61	1500	5.5408
0.1506	1.77	1650	5.3878
0.1904	1.93	1800	5.0405
0.0956	2.09	1950	6.0605
0.0856	2.25	2100	6.1505
0.1206	2.41	2250	5.4903
0.0872	2.58	2400	5.4324
0.1456	2.74	2550	6.1430
0.0848	2.9	2700	5.3999
0.079	3.06	2850	6.0992
0.0706	3.22	3000	6.2144
0.0768	3.38	3150	6.2338
0.0643	3.54	3300	6.0533
0.0576	3.7	3450	5.9912
0.0859	3.86	3600	6.3768
0.0615	4.02	3750	6.1106
0.072	4.19	3900	6.5398
0.0683	4.35	4050	6.5556
0.077	4.51	4200	6.6243
0.0811	4.67	4350	6.5221
0.0591	4.83	4500	6.5732
0.0699	4.99	4650	6.5809

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3