/Chatalet

An extreme-summarisation Natural-Language-Processing model, trained on custom datasets to generate headline of any arbitrarily long article

license tags model-index
apache-2.0
generated_from_keras_callback
name
prikarsartam/Chatelet

prikarsartam/Chatelet

This model is a fine-tuned version of prikarsartam/Chatalet on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 2.6154
  • Validation Loss: 2.4298
  • Train Rouge1: 29.4609
  • Train Rouge2: 8.3437
  • Train Rougel: 23.0867
  • Train Rougelsum: 23.0929
  • Train Gen Len: 18.8153
  • Epoch: 0

Model description

A Seq2Seq model based on Keras model structure with the purpose of extreme-summarisation of any given text of arbitrary inputs; the further plan is to integrate 'multilabel' text classification and 'allure-filter' to enhance performability

Training and evaluation data

Trained on Custom dataset from BBC News Data

Training procedure

It has been trained with 1 epoch with train_loss of 2.6% and will be improved with larger datasets and greated epochs

Training hyperparameters

The following hyperparameters were used during training:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Rouge1 Train Rouge2 Train Rougel Train Rougelsum Train Gen Len Epoch
2.6154 2.4298 29.4609 8.3437 23.0867 23.0929 18.8153 0

Framework versions

  • Transformers 4.21.3
  • TensorFlow 2.8.2
  • Datasets 2.4.0
  • Tokenizers 0.12.1