t5-large-billsum

This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3660
  • Rouge1: 54.3212
  • Rouge2: 34.3078
  • Rougel: 43.7536
  • Rougelsum: 47.5193

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.6948 1.0 1250 1.4332 52.7319 33.508 42.6688 46.3992
1.4965 2.0 2500 1.3864 53.6841 33.9189 43.3753 46.951
1.4333 3.0 3750 1.3707 54.2166 34.2285 43.5537 47.2979
1.4006 4.0 5000 1.3660 54.3212 34.3078 43.7536 47.5193

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.0.2
  • Tokenizers 0.19.1
Downloads last month
16
Safetensors
Model size
738M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for antonkurylo/t5-large-billsum

Base model

google-t5/t5-large
Finetuned
(75)
this model