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metadata
license: mit
base_model: VietAI/vit5-large-vietnews-summarization
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: finetuned-news_summarization_vi
    results: []

Visualize in Weights & Biases

finetuned-news_summarization_vi

This model is a fine-tuned version of VietAI/vit5-large-vietnews-summarization on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2271
  • Rouge1: 0.253
  • Rouge2: 0.1919
  • Rougel: 0.2233
  • Rougelsum: 0.2233
  • Gen Len: 18.496

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: 1
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.2561 1.0 65361 0.2342 0.248 0.1883 0.2192 0.2192 18.274
0.1831 2.0 130722 0.2271 0.253 0.1919 0.2233 0.2233 18.496

Framework versions

  • Transformers 4.43.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1