AraBART-finetuned-ar – AI Model by ahmeddbahaa | AlphaNeural AI

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AraBART-finetuned-ar

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AraBART-finetuned-ar

This model is a fine-tuned version of moussaKam/AraBART on the xlsum dataset. It achieves the following results on the evaluation set:

Loss: 3.7449
Rouge-1: 31.08
Rouge-2: 14.68
Rouge-l: 27.36
Gen Len: 19.64
Bertscore: 73.86

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 10
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge-1	Rouge-2	Rouge-l	Gen Len	Bertscore
4.4318	1.0	2345	3.7996	28.93	13.2	25.56	19.51	73.17
4.0338	2.0	4690	3.7483	30.29	14.24	26.73	19.5	73.59
3.8586	3.0	7035	3.7281	30.44	14.44	26.92	19.75	73.58
3.7289	4.0	9380	3.7204	30.55	14.49	26.88	19.66	73.73
3.6245	5.0	11725	3.7199	30.73	14.63	27.11	19.69	73.68
3.5392	6.0	14070	3.7221	30.85	14.65	27.21	19.7	73.77
3.4694	7.0	16415	3.7286	31.08	14.8	27.41	19.62	73.84
3.4126	8.0	18760	3.7384	31.06	14.77	27.41	19.64	73.82
3.3718	9.0	21105	3.7398	31.18	14.89	27.49	19.67	73.87
3.3428	10.0	23450	3.7449	31.19	14.88	27.44	19.68	73.87

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.1.0
Tokenizers 0.12.1