yt_text_summarizer / README.md
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metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: bart_akshith
    results: []

bart_akshith

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

  • Loss: 1.6098
  • Rouge1: 52.3831
  • Rouge2: 27.5513
  • Rougel: 43.5051
  • Rougelsum: 48.1509
  • Gen Len: 30.1941

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: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.4242 0.9997 1841 1.5158 52.6686 27.364 43.1196 47.9363 30.5824
1.0951 2.0 3683 1.5060 52.8177 27.6542 43.6251 48.207 30.2051
0.8624 2.9997 5524 1.5495 52.6928 28.1014 43.8451 48.4256 28.4212
0.6984 3.9989 7364 1.6098 52.3831 27.5513 43.5051 48.1509 30.1941

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1