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bart-summarizer

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metadata
library_name: transformers
license: mit
base_model: LearneratVnit/bart-summarizer
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: bart-summarizer
    results: []

bart-summarizer

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

  • Loss: 2.3295
  • Rouge1: 0.33
  • Rouge2: 0.0688
  • Rougel: 0.205
  • Rougelsum: 0.2847
  • Gen Len: 129.5045

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
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.4379 0.9992 622 2.3295 0.33 0.0688 0.205 0.2847 129.5045

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1