cnn_news_summary_model_trained_on_reduced_data

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6625
  • Rouge1: 0.2162
  • Rouge2: 0.0943
  • Rougel: 0.183
  • Rougelsum: 0.183
  • Generated Length: 19.0

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: 16
  • eval_batch_size: 16
  • 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 Generated Length
No log 1.0 288 1.6773 0.2168 0.0946 0.1835 0.1836 19.0
1.9303 2.0 576 1.6625 0.2162 0.0943 0.183 0.183 19.0

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
6
Safetensors
Model size
60.5M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for donggyunkim/cnn_news_summary_model_trained_on_reduced_data

Base model

google-t5/t5-small
Finetuned
(1548)
this model

Dataset used to train donggyunkim/cnn_news_summary_model_trained_on_reduced_data

Evaluation results