This model is a fine-tuned version of buianh0803/Text_Summarization on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

Loss: 1.6668
Rouge1: 0.2484
Rouge2: 0.1187
Rougel: 0.2056
Rougelsum: 0.2055
Gen Len: 18.9986

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.8345	1.0	17945	1.6835	0.2475	0.118	0.2047	0.2047	18.998
1.8152	2.0	35890	1.6720	0.2479	0.1179	0.2048	0.2048	18.9986
1.7954	3.0	53835	1.6712	0.2477	0.1182	0.205	0.2051	18.9981
1.7975	4.0	71780	1.6680	0.2482	0.1186	0.2054	0.2054	18.9981
1.7924	5.0	89725	1.6668	0.2484	0.1187	0.2056	0.2055	18.9986

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1

buianh0803/text-sum

text-sum

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

buianh0803/
text-sum