AraT5-base-finetune-ar-wikilingua – AI Model by eslamxm | AlphaNeural AI

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AraT5-base-finetune-ar-wikilingua

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text2text-generation

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text-generation-inference

endpoints_compatible

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AraT5-base-finetune-ar-wikilingua

This model is a fine-tuned version of UBC-NLP/AraT5-base on the wiki_lingua dataset. It achieves the following results on the evaluation set:

Loss: 4.6110
Rouge-1: 19.97
Rouge-2: 6.9
Rouge-l: 18.25
Gen Len: 18.45
Bertscore: 69.44

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: 0.0005
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
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
11.5412	1.0	312	6.8825	5.2	0.69	5.04	19.0	63.2
6.5212	2.0	624	5.8992	8.89	1.4	8.36	17.92	63.9
5.8302	3.0	936	5.3712	9.99	2.21	9.54	15.87	65.08
5.406	4.0	1248	5.0632	13.94	3.5	13.0	15.95	66.83
5.1109	5.0	1560	4.8718	15.28	4.34	14.27	18.26	66.83
4.9004	6.0	1872	4.7631	16.65	4.92	15.46	17.73	67.75
4.754	7.0	2184	4.6920	18.31	5.79	16.9	18.17	68.55
4.6369	8.0	2496	4.6459	18.6	6.12	17.16	18.16	68.66
4.5595	9.0	2808	4.6153	18.94	6.1	17.39	17.82	68.99
4.4967	10.0	3120	4.6110	19.15	6.25	17.55	17.91	69.09

Framework versions

Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1