summarisation_model

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

• Loss: 2.3693
• Rouge1: 0.3115
• Rouge2: 0.1433
• Rougel: 0.2744
• Rougelsum: 0.2741
• Gen Len: 19.957

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• 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	105	2.4604	0.2865	0.125	0.2496	0.2493	19.9403
No log	2.0	210	2.3996	0.3023	0.1376	0.2654	0.2655	19.9379
No log	3.0	315	2.3755	0.3086	0.1422	0.2713	0.2716	19.9332
No log	4.0	420	2.3693	0.3115	0.1433	0.2744	0.2741	19.957

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0