prikarsartam / 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