t5-small-finetuned-wikisql

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

• Loss: 0.1247
• Model Preparation Time: 0.0049
• Rouge1 Precision: 0.873
• Rouge1 Recall: 0.873
• Rouge1 Fmeasure: 0.873
• Rouge2 Precision: 0.7718
• Rouge2 Recall: 0.7718
• Rouge2 Fmeasure: 0.7718
• Rougel Precision: 0.86
• Rougel Recall: 0.86
• Rougel Fmeasure: 0.86

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: 5e-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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Rouge1 Precision	Rouge1 Recall	Rouge1 Fmeasure	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure	Rougel Precision	Rougel Recall	Rougel Fmeasure
0.1942	1.0	4049	0.1561	0.0049	0.8629	0.8629	0.8629	0.7471	0.7471	0.7471	0.8471	0.8471	0.8471
0.1646	2.0	8098	0.1373	0.0049	0.8697	0.8697	0.8697	0.763	0.763	0.763	0.8555	0.8555	0.8555
0.147	3.0	12147	0.1297	0.0049	0.8723	0.8723	0.8723	0.7684	0.7684	0.7684	0.8588	0.8588	0.8588
0.1412	4.0	16196	0.1256	0.0049	0.8725	0.8725	0.8725	0.7712	0.7712	0.7712	0.8595	0.8595	0.8595
0.14	5.0	20245	0.1247	0.0049	0.873	0.873	0.873	0.7718	0.7718	0.7718	0.86	0.86	0.86

Framework versions

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