ainize-kobart-news-eb-finetuned-papers – AI Model by eunbeee | AlphaNeural AI

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eunbeee/
ainize-kobart-news-eb-finetuned-papers

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ainize-kobart-news-eb-finetuned-papers

This model is a fine-tuned version of ainize/kobart-news on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3066
Rouge1: 14.5433
Rouge2: 5.2238
Rougel: 14.4731
Rougelsum: 14.5183
Gen Len: 19.9934

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: 4
eval_batch_size: 4
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
0.1918	1.0	7200	0.2403	14.6883	5.2427	14.6306	14.6489	19.9938
0.1332	2.0	14400	0.2391	14.5165	5.2443	14.493	14.4908	19.9972
0.0966	3.0	21600	0.2539	14.758	5.4976	14.6906	14.7188	19.9941
0.0736	4.0	28800	0.2782	14.6267	5.3371	14.5578	14.6014	19.9934
0.0547	5.0	36000	0.3066	14.5433	5.2238	14.4731	14.5183	19.9934

Framework versions

Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1