summarization_model

This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.8757
• Rouge1: 0.394
• Rouge2: 0.166
• Rougel: 0.3264
• Rougelsum: 0.3263
• Gen Len: 16.3055

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	389	1.9453	0.3776	0.1556	0.3135	0.3136	15.9023
2.2585	2.0	778	1.8995	0.3864	0.1602	0.3209	0.321	16.1286
2.1003	3.0	1167	1.8807	0.3926	0.1654	0.3256	0.3256	16.1897
2.064	4.0	1556	1.8757	0.394	0.166	0.3264	0.3263	16.3055

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1