t5-small-finetuned-wikisql
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1196
- Rouge2 Precision: 0.542
- Rouge2 Recall: 0.5311
- Rouge2 Fmeasure: 0.5337
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.2028 | 1.0 | 34700 | 0.1694 | 0.418 | 0.4091 | 0.4102 |
| 0.1681 | 2.0 | 69400 | 0.1396 | 0.4921 | 0.48 | 0.483 |
| 0.152 | 3.0 | 104100 | 0.1274 | 0.5227 | 0.511 | 0.5139 |
| 0.145 | 4.0 | 138800 | 0.1212 | 0.5367 | 0.5258 | 0.5284 |
| 0.1383 | 5.0 | 173500 | 0.1196 | 0.542 | 0.5311 | 0.5337 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.