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Imask/BART_Lagre_2000samples_without_format
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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: Large_2000samples_new_without_format
    results: []

Large_2000samples_new_without_format

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

  • Loss: 1.6015
  • Model Preparation Time: 0.0208
  • Rouge1: 75.395
  • Rouge2: 67.875
  • Rougel: 60.2432
  • Rougelsum: 74.8264
  • Gen Len: 104.49

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 2
  • label_smoothing_factor: 0.1

Training results

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1