Edit model card

bart-samsum

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

  • Loss: 1.3852
  • Rouge1: 0.547
  • Rouge2: 0.2837
  • Rougel: 0.4462
  • Rougelsum: 0.4454
  • Gen Len: 29.72

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.5201 0.27 500 1.4589 0.5276 0.2694 0.4246 0.424 33.5067
1.3757 0.54 1000 1.5105 0.506 0.2566 0.415 0.4146 29.76
1.3496 0.81 1500 1.4039 0.5365 0.2759 0.4233 0.4221 29.8
1.094 1.09 2000 1.4119 0.5407 0.2827 0.4293 0.4288 29.84
1.1488 1.36 2500 1.3680 0.5275 0.2637 0.423 0.4224 26.92
1.1222 1.63 3000 1.2875 0.5369 0.2844 0.4473 0.4463 29.2267
1.1092 1.9 3500 1.3968 0.533 0.2818 0.4354 0.4363 30.0667
0.8509 2.17 4000 1.3682 0.5306 0.2874 0.4327 0.4331 29.1467
0.9565 2.44 4500 1.3450 0.5466 0.2782 0.4419 0.4409 29.2133
0.8496 2.72 5000 1.3768 0.5366 0.2807 0.4359 0.4351 30.7733
0.8397 2.99 5500 1.3852 0.547 0.2837 0.4462 0.4454 29.72

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
Downloads last month
6
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Venkatesh4342/bart-samsum

Finetuned
(50)
this model

Dataset used to train Venkatesh4342/bart-samsum

Evaluation results