---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: ALL_mt5-base_15_wikiSQL_no_sch
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ALL_mt5-base_15_wikiSQL_no_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: 0.1014
- Rouge2 Precision: 0.774
- Rouge2 Recall: 0.7029
- Rouge2 Fmeasure: 0.731

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.1507        | 1.0   | 8637   | 0.1284          | 0.7172           | 0.6444        | 0.673           |
| 0.1214        | 2.0   | 17274  | 0.1125          | 0.7391           | 0.6666        | 0.6954          |
| 0.1049        | 3.0   | 25911  | 0.1070          | 0.7514           | 0.6775        | 0.7069          |
| 0.0951        | 4.0   | 34548  | 0.1035          | 0.7558           | 0.6832        | 0.712           |
| 0.0893        | 5.0   | 43185  | 0.1019          | 0.7627           | 0.6903        | 0.7189          |
| 0.0854        | 6.0   | 51822  | 0.1010          | 0.766            | 0.6933        | 0.7222          |
| 0.0794        | 7.0   | 60459  | 0.1001          | 0.7672           | 0.6951        | 0.7237          |
| 0.0719        | 8.0   | 69096  | 0.0999          | 0.7703           | 0.698         | 0.7267          |
| 0.0713        | 9.0   | 77733  | 0.1002          | 0.77             | 0.6983        | 0.7268          |
| 0.067         | 10.0  | 86370  | 0.1004          | 0.7726           | 0.7006        | 0.7291          |
| 0.0649        | 11.0  | 95007  | 0.1005          | 0.773            | 0.7017        | 0.7299          |
| 0.0636        | 12.0  | 103644 | 0.1009          | 0.7733           | 0.7018        | 0.7301          |
| 0.0614        | 13.0  | 112281 | 0.1009          | 0.7735           | 0.7021        | 0.7303          |
| 0.0608        | 14.0  | 120918 | 0.1012          | 0.7737           | 0.7028        | 0.7308          |
| 0.06          | 15.0  | 129555 | 0.1014          | 0.774            | 0.7029        | 0.731           |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1