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mbert2mbert-finetuned-ar-wikilingua – AI Model by eslamxm | AlphaNeural AI
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mbert2mbert-finetuned-ar-wikilingua
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transformers
pytorch
tensorboard
encoder-decoder
text2text-generation
summarization
ar
mbert
mbert2mbert
Abstractive Summarization
generated_from_trainer
wiki_lingua
endpoints_compatible
us
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mbert2mbert-finetuned-ar-wikilingua
This model is a fine-tuned version of
on the wiki_lingua dataset. It achieves the following results on the evaluation set:
Loss: 3.6753
Rouge-1: 15.19
Rouge-2: 5.45
Rouge-l: 14.64
Gen Len: 20.0
Bertscore: 67.86
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 8
label_smoothing_factor: 0.1
Training results
Framework versions
Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1
