resume6 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - multi_news
metrics:
  - rouge
model-index:
  - name: resume6
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: multi_news
          type: multi_news
          config: default
          split: test
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 22.17621046093242

resume6

This model is a fine-tuned version of AKbuyer/resume5 on the multi_news dataset. It achieves the following results on the evaluation set:

  • Loss: 2.9796
  • Rouge1: 22.1762
  • Rouge2: 6.6459
  • Rougel: 18.3710
  • Rougelsum: 18.3626
  • Gen Len: 1893.4899

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: 5e-07
  • 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: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.3348 1.0 5622 3.0918 21.3362 6.1922 17.7104 17.6992 1893.0630
3.2854 2.0 11244 3.0466 21.6506 6.3791 17.9362 17.9246 1891.6044
3.2205 3.0 16866 3.0200 21.8475 6.4847 18.0981 18.0882 1892.4760
3.2251 4.0 22488 3.0029 22.0082 6.5196 18.2405 18.2301 1892.9385
3.2348 5.0 28110 2.9916 22.1078 6.5975 18.3134 18.2985 1893.3298
3.2257 6.0 33732 2.9845 22.1627 6.6119 18.3677 18.3496 1893.5788
3.2106 7.0 39354 2.9806 22.1825 6.6472 18.3798 18.3664 1893.5432
3.22 8.0 44976 2.9796 22.1762 6.6459 18.3710 18.3626 1893.4899

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3