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led-risalah_data_v11

This model is a fine-tuned version of silmi224/finetune-led-35000 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6843
  • Rouge1 Precision: 0.7035
  • Rouge1 Recall: 0.1205
  • Rouge1 Fmeasure: 0.2038

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Precision Rouge1 Recall Rouge1 Fmeasure
2.6071 0.9714 17 1.8938 0.6021 0.1074 0.1803
1.745 2.0 35 1.7661 0.7095 0.1174 0.1994
1.5717 2.9714 52 1.7251 0.6704 0.1176 0.1968
1.4921 4.0 70 1.6772 0.7014 0.1175 0.1986
1.3932 4.9714 87 1.6745 0.7008 0.1187 0.2011
1.3002 6.0 105 1.6869 0.6913 0.1196 0.2012
1.2784 6.9714 122 1.6857 0.7114 0.1246 0.2097
1.1779 7.7714 136 1.6843 0.7035 0.1205 0.2038

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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