Edit model card

led-base-16384-finetuned-summscreen-bestval-100-genlen-10-epochs

This model is a fine-tuned version of allenai/led-base-16384 on the SummScreen dataset. It achieves the following results on the evaluation set:

  • Loss: 3.1833
  • Rouge1: 31.6225
  • Rouge2: 6.7688
  • Rougel: 18.5526
  • Rougelsum: 27.3033
  • Gen Len: 81.8209

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: 1e-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
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.1147 0.99 3500 3.0409 30.2997 6.0055 17.6836 26.3062 92.0363
2.7805 1.99 7000 2.9981 31.0651 6.1553 18.2326 26.6136 84.1678
2.6362 2.98 10500 3.0013 31.0598 6.4268 18.3805 26.7816 81.1338
2.4646 3.98 14000 3.0267 31.46 6.5898 18.5842 27.165 83.4966
2.2546 4.97 17500 3.0448 31.4952 6.3709 18.2124 27.111 86.1701
2.1432 5.97 21000 3.0840 31.6475 6.663 18.504 27.2444 81.3583
2.0585 6.96 24500 3.1105 31.3432 6.7862 18.4461 27.0081 76.4671
1.9243 7.96 28000 3.1558 31.5712 6.6456 18.3928 27.2066 81.1769
1.8828 8.95 31500 3.1686 31.6361 6.4783 18.4167 27.2049 83.0658
1.8403 9.95 35000 3.1833 31.6225 6.7688 18.5526 27.3033 81.8209

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1
  • Datasets 2.9.0
  • Tokenizers 0.13.2
Downloads last month
3
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Space using JulianS/led-base-16384-finetuned-summscreen 1