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bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-10-1

This model is a fine-tuned version of Ameer05/model-token-repo on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4855
  • Rouge1: 58.3832
  • Rouge2: 49.9973
  • Rougel: 55.3055
  • Rougelsum: 57.7139

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-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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
No log 0.91 5 2.0183 52.3098 45.5304 49.2759 51.7456
No log 1.91 10 1.6564 61.815 53.9035 58.4243 60.784
No log 2.91 15 1.5330 61.3032 54.12 58.9152 60.7178
No log 3.91 20 1.4539 63.3012 56.2987 61.0907 62.5217
1.5646 4.91 25 1.4578 62.4815 55.1453 60.3921 61.6067
1.5646 5.91 30 1.4284 61.5347 54.1271 58.8474 60.5427
1.5646 6.91 35 1.4467 61.5081 53.8512 59.2782 60.6928
1.5646 7.91 40 1.4653 59.5349 51.8208 56.5996 58.8211
0.6692 8.91 45 1.4740 57.2917 49.5416 54.8409 56.6276
0.6692 9.91 50 1.4855 58.3832 49.9973 55.3055 57.7139

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.9.1
  • Datasets 1.18.4
  • Tokenizers 0.10.3
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