transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: ALL_mt5-base_15_wikiSQL
  results: []
---

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# ALL_mt5-base_15_wikiSQL

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2022
- Rouge2 Precision: 0.7669
- Rouge2 Recall: 0.6952
- Rouge2 Fmeasure: 0.7236

## 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: 40
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.322         | 1.0   | 3239  | 0.2649          | 0.7077           | 0.6357        | 0.6638          |
| 0.2728        | 2.0   | 6478  | 0.2361          | 0.7294           | 0.657         | 0.6857          |
| 0.2353        | 3.0   | 9717  | 0.2220          | 0.7396           | 0.6677        | 0.6962          |
| 0.2192        | 4.0   | 12956 | 0.2159          | 0.7491           | 0.6752        | 0.7046          |
| 0.2044        | 5.0   | 16195 | 0.2106          | 0.7521           | 0.6797        | 0.7084          |
| 0.1916        | 6.0   | 19434 | 0.2076          | 0.7558           | 0.6841        | 0.7125          |
| 0.1815        | 7.0   | 22673 | 0.2059          | 0.759            | 0.6869        | 0.7155          |
| 0.1713        | 8.0   | 25912 | 0.2050          | 0.7612           | 0.6896        | 0.7179          |
| 0.1705        | 9.0   | 29151 | 0.2034          | 0.7644           | 0.6917        | 0.7206          |
| 0.1652        | 10.0  | 32390 | 0.2042          | 0.7649           | 0.6928        | 0.7214          |
| 0.16          | 11.0  | 35629 | 0.2026          | 0.7661           | 0.6938        | 0.7225          |
| 0.1534        | 12.0  | 38868 | 0.2022          | 0.7659           | 0.694         | 0.7225          |
| 0.1516        | 13.0  | 42107 | 0.2024          | 0.7671           | 0.695         | 0.7236          |
| 0.1517        | 14.0  | 45346 | 0.2024          | 0.7667           | 0.6951        | 0.7235          |
| 0.1503        | 15.0  | 48585 | 0.2022          | 0.7669           | 0.6952        | 0.7236          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
