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metadata
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: BART-Large-psychological-dataset
    results: []

BART-Large-psychological-dataset

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

  • Loss: 1.1549
  • Rouge1: 0.6621
  • Rouge2: 0.4488
  • Rougel: 0.5658
  • Rougelsum: 0.5656
  • Gen Len: 80.6204

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 274 0.8651 0.6252 0.3953 0.5206 0.5206 86.9982
0.7484 2.0 548 0.8332 0.648 0.4301 0.554 0.5541 79.885
0.7484 3.0 822 0.8943 0.6498 0.4335 0.5514 0.5518 82.635
0.3207 4.0 1096 0.9653 0.6571 0.4422 0.5607 0.5609 79.9708
0.3207 5.0 1370 1.0514 0.6582 0.4445 0.5637 0.5639 79.8047
0.1557 6.0 1644 1.0752 0.6607 0.4476 0.5659 0.5657 79.6058
0.1557 7.0 1918 1.1302 0.6588 0.4443 0.5626 0.5626 80.5821
0.0845 8.0 2192 1.1549 0.6621 0.4488 0.5658 0.5656 80.6204

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1