text-sum-3

This model is a fine-tuned version of buianh0803/text-sum-2 on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

• Loss: 1.6546
• Rouge1: 0.2475
• Rouge2: 0.1177
• Rougel: 0.2051
• Rougelsum: 0.2051
• Gen Len: 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: 0.001
• 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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.8082	1.0	17945	1.6546	0.2475	0.1177	0.2051	0.2051	19.0

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1