bigbird_lora_multi_lexsum

This model is a fine-tuned version of google/bigbird-pegasus-large-bigpatent on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 9.1007
  • Rouge1: 0.197
  • Rouge2: 0.0165
  • Rougel: 0.1446
  • Rougelsum: 0.1445
  • Gen Len: 235.208

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: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
9.2003 1.0 850 9.1012 0.1982 0.0162 0.1439 0.1441 234.016
9.151 2.0 1700 9.1007 0.197 0.0165 0.1446 0.1445 235.208

Framework versions

  • PEFT 0.10.0
  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
0
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for Rud/bigbird_lora_multi_lexsum

Adapter
(3)
this model