bart-base-xsum / README.md
Moreno La Quatra
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: bart-base-xsum
    results: []

bart-base-xsum

This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8051
  • R1: 0.5643
  • R2: 0.3017
  • Rl: 0.5427
  • Rlsum: 0.5427

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss R1 R2 Rl Rlsum
0.8983 1.0 6377 0.8145 0.5443 0.2724 0.5212 0.5211
0.8211 2.0 12754 0.7940 0.5519 0.2831 0.5295 0.5295
0.7701 3.0 19131 0.7839 0.5569 0.2896 0.5347 0.5348
0.7046 4.0 25508 0.7792 0.5615 0.2956 0.5394 0.5393
0.6837 5.0 31885 0.7806 0.5631 0.2993 0.5416 0.5416
0.6412 6.0 38262 0.7816 0.5643 0.301 0.5427 0.5426
0.6113 7.0 44639 0.7881 0.5645 0.3017 0.5428 0.5428
0.5855 8.0 51016 0.7921 0.5651 0.303 0.5433 0.5432
0.5636 9.0 57393 0.7972 0.5649 0.3032 0.5433 0.5433
0.5482 10.0 63770 0.7996 0.565 0.3036 0.5436 0.5435

Framework versions

  • Transformers 4.22.1
  • Pytorch 1.11.0+cu113
  • Datasets 2.0.0
  • Tokenizers 0.11.6