led_model

This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4363
  • Rouge1: 0.7117
  • Rouge2: 0.5663
  • Rougel: 0.684
  • Rougelsum: 0.6843
  • Gen Len: 15.7955

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.6184 0.9995 546 0.4788 0.699 0.5474 0.6691 0.6694 15.7362
0.4523 1.9991 1092 0.4435 0.7029 0.5569 0.6773 0.6773 15.6763
0.3732 2.9986 1638 0.4392 0.7104 0.565 0.6826 0.6827 15.8442
0.3249 3.9982 2184 0.4363 0.7117 0.5663 0.684 0.6843 15.7955

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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