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

model

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

  • Loss: 1.5537

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.9566 0.08 500 1.7765
1.9288 0.16 1000 1.7549
1.8561 0.24 1500 1.7462
1.7802 0.31 2000 1.6921
1.8444 0.39 2500 1.6699
1.8145 0.47 3000 1.6525
1.7736 0.55 3500 1.6313
1.7259 0.63 4000 1.6234
1.7028 0.71 4500 1.6217
1.7235 0.78 5000 1.5750
1.6534 0.86 5500 1.5749
1.6392 0.94 6000 1.5537

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.10.1
  • Tokenizers 0.13.2