mtc / bart-base-govreport-1024

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Total runs: 5
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7-day runs: 2
30-day runs: 0
Model's Last Updated: February 14 2024
text-generation

Introduction of bart-base-govreport-1024

Model Details of bart-base-govreport-1024

bart-base-govreport-1024

This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 4.5326
  • Rouge1: 47.2014
  • Rouge2: 14.3537
  • Rougel: 20.357
  • Rougelsum: 45.2941
  • Gen Len: 748.32
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: 0.0008
  • train_batch_size: 8
  • eval_batch_size: 4
  • 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: polynomial
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 4
  • mixed_precision_training: Native AMP
  • label_smoothing_factor: 0.2
Training results
Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
4.7807 1.83 1000 4.7100 44.714 12.3085 18.8368 42.8279 749.72
4.4195 3.65 2000 4.5326 47.2014 14.3537 20.357 45.2941 748.32
Framework versions
  • Transformers 4.37.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.15.2

Runs of mtc bart-base-govreport-1024 on huggingface.co

5
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3-day runs
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7-day runs
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Updated:February 14 2024