---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: ALL_mt5-base_15_wikiSQL_sch
  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. -->

# ALL_mt5-base_15_wikiSQL_sch

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0585
- Rouge2 Precision: 0.8836
- Rouge2 Recall: 0.8038
- Rouge2 Fmeasure: 0.8358

## 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: 15
- eval_batch_size: 15
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.0796        | 1.0   | 8637   | 0.0675          | 0.8604           | 0.78          | 0.8122          |
| 0.0683        | 2.0   | 17274  | 0.0617          | 0.8681           | 0.7878        | 0.8199          |
| 0.0587        | 3.0   | 25911  | 0.0593          | 0.8733           | 0.7924        | 0.8248          |
| 0.0527        | 4.0   | 34548  | 0.0579          | 0.8776           | 0.795         | 0.8282          |
| 0.0478        | 5.0   | 43185  | 0.0573          | 0.8788           | 0.7981        | 0.8305          |
| 0.0453        | 6.0   | 51822  | 0.0571          | 0.8806           | 0.7999        | 0.8323          |
| 0.043         | 7.0   | 60459  | 0.0571          | 0.8816           | 0.8008        | 0.8333          |
| 0.0399        | 8.0   | 69096  | 0.0570          | 0.881            | 0.8006        | 0.8329          |
| 0.0389        | 9.0   | 77733  | 0.0573          | 0.8823           | 0.8019        | 0.8343          |
| 0.0363        | 10.0  | 86370  | 0.0573          | 0.8828           | 0.8025        | 0.8347          |
| 0.0366        | 11.0  | 95007  | 0.0580          | 0.8835           | 0.8028        | 0.8352          |
| 0.0333        | 12.0  | 103644 | 0.0579          | 0.8836           | 0.8032        | 0.8355          |
| 0.0325        | 13.0  | 112281 | 0.0581          | 0.8833           | 0.8036        | 0.8356          |
| 0.0327        | 14.0  | 120918 | 0.0585          | 0.8839           | 0.8039        | 0.836           |
| 0.0306        | 15.0  | 129555 | 0.0585          | 0.8836           | 0.8038        | 0.8358          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1