AraBART-finetuned-wiki-ar – AI Model by Jezia | AlphaNeural AI

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Jezia/
AraBART-finetuned-wiki-ar

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text2text-generation

endpoints_compatible

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AraBART-finetuned-wiki-ar

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

Loss: 2.4030
Rouge1: 0.9862
Rouge2: 0.2292
Rougel: 0.9902
Rougelsum: 0.9847
Gen Len: 19.3511

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.8633	1.0	2556	2.5599	0.7861	0.1289	0.7656	0.7721	19.2354
2.6525	2.0	5112	2.4824	0.7315	0.2374	0.7224	0.7357	19.261
2.5068	3.0	7668	2.4404	0.7772	0.2114	0.7671	0.7861	19.3035
2.4251	4.0	10224	2.4269	0.7464	0.2156	0.745	0.7504	19.2929
2.3739	5.0	12780	2.4119	0.7642	0.1879	0.7729	0.7774	19.3573
2.275	6.0	15336	2.4039	0.9048	0.1952	0.9198	0.9189	19.37
2.2787	7.0	17892	2.4007	0.9913	0.2278	0.9951	1.0038	19.335
2.2142	8.0	20448	2.4073	0.9736	0.238	0.9697	0.9773	19.3556
2.1852	9.0	23004	2.4007	0.9825	0.2322	0.9891	0.9962	19.3213
2.1597	10.0	25560	2.4030	0.9862	0.2292	0.9902	0.9847	19.3511

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2