flux-dsum

This model is a fine-tuned version of cointegrated/rut5-base-absum on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3535
  • Rouge1: 0.3631
  • Rouge2: 0.1695
  • Rougel: 0.325
  • Rougelsum: 0.3251
  • Gen Len: 18.2008

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: 2
  • eval_batch_size: 2
  • 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 Gen Len
1.7402 1.0 21753 1.4456 0.3492 0.1601 0.3112 0.3114 18.0104
1.59 2.0 43506 1.3912 0.3569 0.1616 0.3186 0.3187 18.1955
1.5522 3.0 65259 1.3675 0.3607 0.1682 0.3231 0.3233 18.1123
1.5162 4.0 87012 1.3535 0.3631 0.1695 0.325 0.3251 18.2008

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1
Downloads last month
13
Safetensors
Model size
244M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for thefluxapp/rut5-base-dsum

Finetuned
(2)
this model