amb-dataset-factor / README.md
Zohaib002's picture
End of training
28e0bda verified
metadata
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: amb-dataset-factor
    results: []

amb-dataset-factor

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: 0.8578
  • Rouge1: 0.6039
  • Rouge2: 0.3487
  • Rougel: 0.4805
  • Rougelsum: 0.4805
  • Gen Len: 101.0

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 1 1.1889 0.5926 0.2701 0.3828 0.3828 65.5
No log 2.0 2 1.0179 0.6489 0.3333 0.458 0.458 77.5
No log 3.0 3 0.9405 0.6084 0.2627 0.3783 0.3783 82.5
No log 4.0 4 0.8990 0.6241 0.3058 0.4054 0.4054 86.0
No log 5.0 5 0.8814 0.6746 0.3882 0.4842 0.4842 95.0
No log 6.0 6 0.8679 0.5554 0.3111 0.4127 0.4127 94.5
No log 7.0 7 0.8607 0.5799 0.3016 0.4153 0.4153 100.0
No log 8.0 8 0.8578 0.6039 0.3487 0.4805 0.4805 101.0

Framework versions

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