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mbert2mbert-finetune-fa – AI Model by eslamxm | AlphaNeural AI

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eslamxm/
mbert2mbert-finetune-fa

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encoder-decoder

text2text-generation

Abstractive Summarization

generated_from_trainer

endpoints_compatible

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mbert2mbert-finetune-fa

This model is a fine-tuned version of on the pn_summary dataset.

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: 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: 5
label_smoothing_factor: 0.1

Training results

Framework versions

Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1