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metadata
base_model: silmi224/finetune-led-35000
tags:
  - summarization
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: led-risalah_data_v17_3
    results: []

led-risalah_data_v17_3

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: 1.6551
  • Rouge1: 25.33
  • Rouge2: 12.4758
  • Rougel: 18.3801
  • Rougelsum: 24.0275

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: 1e-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
  • lr_scheduler_warmup_steps: 200
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.9826 1.0 20 2.5250 11.8736 3.4553 8.0701 10.4233
2.5516 2.0 40 2.2001 15.7664 5.0213 10.8555 14.1975
2.2334 3.0 60 2.0424 17.0425 6.006 10.956 15.2795
1.9577 4.0 80 1.9305 19.1792 7.6754 12.651 17.7519
1.8602 5.0 100 1.8351 22.4846 8.3095 14.0022 20.587
1.702 6.0 120 1.7809 21.9395 8.5042 14.9427 20.3436
1.6525 7.0 140 1.7286 23.7825 10.9231 15.9319 22.0902
1.5285 8.0 160 1.6839 24.1286 11.2382 16.7057 22.3731
1.4623 9.0 180 1.6644 23.8767 12.3834 17.5761 22.6869
1.4175 10.0 200 1.6551 25.33 12.4758 18.3801 24.0275

Framework versions

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