led-large-16384-finetune-paperLedWeSAttG0.1

This model is a fine-tuned version of allenai/led-large-16384 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.9013
• Rouge1: 35.4319
• Rouge2: 9.1043
• Rougel: 16.1054
• Rougelsum: 33.675
• Gen Len: 1.0

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.9556	0.9993	1128	3.0039	35.2679	8.0717	17.8571	33.4821	1.0
2.7602	1.9993	2256	2.9080	35.0731	6.7086	17.5365	32.9854	1.0
2.63	2.9993	3384	2.9013	35.4319	9.1043	16.1054	33.675	1.0

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.1