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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: ALL_mt5-base_10_wikiSQL
  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_10_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: 0.2056
- Rouge2 Precision: 0.7601
- Rouge2 Recall: 0.6878
- Rouge2 Fmeasure: 0.7165

## 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: 35
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.3197        | 1.0   | 3702  | 0.2658          | 0.7084           | 0.6348        | 0.6636          |
| 0.2666        | 2.0   | 7404  | 0.2348          | 0.7294           | 0.6574        | 0.686           |
| 0.2356        | 3.0   | 11106 | 0.2229          | 0.7409           | 0.6678        | 0.6968          |
| 0.2169        | 4.0   | 14808 | 0.2162          | 0.7471           | 0.6747        | 0.7035          |
| 0.2021        | 5.0   | 18510 | 0.2121          | 0.7513           | 0.6796        | 0.708           |
| 0.1959        | 6.0   | 22212 | 0.2089          | 0.7545           | 0.6824        | 0.711           |
| 0.1878        | 7.0   | 25914 | 0.2069          | 0.757            | 0.6848        | 0.7134          |
| 0.1801        | 8.0   | 29616 | 0.2060          | 0.7586           | 0.6862        | 0.715           |
| 0.1763        | 9.0   | 33318 | 0.2055          | 0.7594           | 0.6877        | 0.7161          |
| 0.1752        | 10.0  | 37020 | 0.2056          | 0.7601           | 0.6878        | 0.7165          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3