mbart-large-50-finetuned-persian – AI Model by ahmeddbahaa | AlphaNeural AI

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ahmeddbahaa/
mbart-large-50-finetuned-persian

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text2text-generation

Abstractive Summarization

generated_from_trainer

endpoints_compatible

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mbart-large-50-finetuned-persian

This model is a fine-tuned version of facebook/mbart-large-50 on the xlsum dataset. It achieves the following results on the evaluation set:

Loss: 4.1932
Rouge-1: 26.11
Rouge-2: 8.11
Rouge-l: 21.09
Gen Len: 37.29
Bertscore: 71.08

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: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge-1	Rouge-2	Rouge-l	Gen Len	Bertscore
5.5612	1.0	1476	4.5015	17.07	3.14	13.54	47.49	66.83
4.3049	2.0	2952	4.1055	22.63	5.89	18.03	40.43	69.23
3.8154	3.0	4428	3.9822	24.57	7.15	19.74	37.35	70.36
3.3401	4.0	5904	4.0088	25.84	7.96	20.95	37.56	70.83
2.8879	5.0	7380	4.1932	26.24	8.26	21.23	37.78	71.05

Framework versions

Transformers 4.19.1
Pytorch 1.11.0+cu113
Datasets 2.2.1
Tokenizers 0.12.1