metadata

library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - wikisql
model-index:
  - name: t5-small-finetuned-wikisql
    results: []

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