multinews_model

This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.2447
• Rouge1: 0.1541
• Rouge2: 0.0514
• Rougel: 0.1178
• Rougelsum: 0.1178
• Gen Len: 18.9996

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.508	1.0	1406	2.2746	0.1525	0.0501	0.1164	0.1164	18.9972
2.4136	2.0	2812	2.2489	0.1535	0.0512	0.1173	0.1173	18.9996
2.3479	3.0	4218	2.2447	0.1541	0.0514	0.1178	0.1178	18.9996

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2