Edit model card

theus_concepttagger

This model is a fine-tuned version of facebook/bart-large-cnn on the xsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6249
  • Rouge1: 34.8663
  • Rouge2: 15.1526
  • Rougel: 26.1224
  • Rougelsum: 26.5164
  • Gen Len: 62.4475

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.4096 1.0 12753 1.6249 34.8663 15.1526 26.1224 26.5164 62.4475

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
Downloads last month
70
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.

Model tree for namanpundir/theus_concepttagger

Finetuned
(295)
this model

Dataset used to train namanpundir/theus_concepttagger

Space using namanpundir/theus_concepttagger 1

Evaluation results