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---
tags:
- generated_from_trainer
model-index:
- name: EN_mrm8488_spider
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# EN_mrm8488_spider
This model is a fine-tuned version of [mrm8488/t5-small-finetuned-wikiSQL](https://huggingface.co/mrm8488/t5-small-finetuned-wikiSQL) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1002
- Rouge2 Precision: 0.0364
- Rouge2 Recall: 0.0288
- Rouge2 Fmeasure: 0.0266
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log | 1.0 | 438 | 0.4103 | 0.3532 | 0.1547 | 0.194 |
| 0.9639 | 2.0 | 876 | 0.2544 | 0.189 | 0.086 | 0.1038 |
| 0.3388 | 3.0 | 1314 | 0.1954 | 0.1365 | 0.0641 | 0.0768 |
| 0.2255 | 4.0 | 1752 | 0.1614 | 0.0644 | 0.0377 | 0.0407 |
| 0.1673 | 5.0 | 2190 | 0.1412 | 0.0675 | 0.0443 | 0.0467 |
| 0.1356 | 6.0 | 2628 | 0.1344 | 0.0528 | 0.0361 | 0.0366 |
| 0.1148 | 7.0 | 3066 | 0.1255 | 0.0476 | 0.0333 | 0.0338 |
| 0.0998 | 8.0 | 3504 | 0.1167 | 0.0513 | 0.0389 | 0.0374 |
| 0.0998 | 9.0 | 3942 | 0.1107 | 0.0619 | 0.0447 | 0.0439 |
| 0.088 | 10.0 | 4380 | 0.1092 | 0.0529 | 0.0412 | 0.0384 |
| 0.0816 | 11.0 | 4818 | 0.1047 | 0.0478 | 0.0358 | 0.0334 |
| 0.0742 | 12.0 | 5256 | 0.1015 | 0.0386 | 0.0306 | 0.028 |
| 0.071 | 13.0 | 5694 | 0.1018 | 0.0384 | 0.0301 | 0.0281 |
| 0.0674 | 14.0 | 6132 | 0.1004 | 0.0344 | 0.0279 | 0.0256 |
| 0.0674 | 15.0 | 6570 | 0.1002 | 0.0364 | 0.0288 | 0.0266 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
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