opt350m-lora-billsum-1

This model is a fine-tuned version of facebook/opt-350m on an unknown dataset.

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: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Evaluation Results (Validation): {'rouge1': 0.3226, 'rouge2': 0.1138, 'rougeL': 0.2143, 'rougeLsum': 0.2374}

Evaluation Results (Test): {'rouge1': 0.4778, 'rouge2': 0.2811, 'rougeL': 0.3785, 'rougeLsum': 0.3992}

Framework versions

  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.21.0
Downloads last month
6
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for clee9/opt350m-lora-billsum-1

Base model

facebook/opt-350m
Adapter
(108)
this model