TextSummarizerAI_Basic_v1

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

• Loss: 2.3319
• Rouge1: 0.1985
• Rouge2: 0.1019
• Rougel: 0.1702
• Rougelsum: 0.17
• 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: 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: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	62	2.7851	0.1315	0.0434	0.1122	0.1124	19.0
No log	2.0	124	2.5568	0.1442	0.0559	0.1197	0.1193	19.0
No log	3.0	186	2.4669	0.1536	0.062	0.127	0.1268	19.0
No log	4.0	248	2.4149	0.1768	0.0786	0.1472	0.1472	19.0
No log	5.0	310	2.3847	0.1947	0.0959	0.1653	0.1651	19.0
No log	6.0	372	2.3634	0.1973	0.0999	0.1691	0.1688	19.0
No log	7.0	434	2.3487	0.1981	0.1017	0.1704	0.1703	19.0
No log	8.0	496	2.3404	0.1982	0.102	0.1706	0.1703	19.0
2.7541	9.0	558	2.3333	0.199	0.1024	0.1711	0.1709	19.0
2.7541	10.0	620	2.3319	0.1985	0.1019	0.1702	0.17	19.0

Framework versions

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