theus_concepttagger / README.md
Naman Pundir
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metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: theus_concepttagger
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          config: default
          split: validation
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 34.8663

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