---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: EN_mt5-base_15_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_mt5-base_15_spider

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: 0.4677
- Rouge2 Precision: 0.5384
- Rouge2 Recall: 0.3712
- Rouge2 Fmeasure: 0.413

## 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  | 1.7721          | 0.0              | 0.0           | 0.0             |
| 10.9203       | 2.0   | 876  | 1.5463          | 0.0048           | 0.0008        | 0.0015          |
| 1.7683        | 3.0   | 1314 | 1.3623          | 0.0164           | 0.0008        | 0.0014          |
| 1.6091        | 4.0   | 1752 | 1.0649          | 0.0036           | 0.0012        | 0.0014          |
| 1.2253        | 5.0   | 2190 | 0.3614          | 0.2985           | 0.1906        | 0.2088          |
| 0.3973        | 6.0   | 2628 | 0.3133          | 0.4588           | 0.2914        | 0.3317          |
| 0.2032        | 7.0   | 3066 | 0.3007          | 0.5065           | 0.3375        | 0.3799          |
| 0.1597        | 8.0   | 3504 | 0.3109          | 0.5212           | 0.3579        | 0.3988          |
| 0.1597        | 9.0   | 3942 | 0.3431          | 0.5194           | 0.3529        | 0.3931          |
| 0.1385        | 10.0  | 4380 | 0.4681          | 0.5315           | 0.3636        | 0.4051          |
| 0.1285        | 11.0  | 4818 | 0.5505          | 0.5331           | 0.3666        | 0.4074          |
| 0.1228        | 12.0  | 5256 | 0.5351          | 0.5331           | 0.3645        | 0.4063          |
| 0.1092        | 13.0  | 5694 | 0.4808          | 0.5355           | 0.3697        | 0.4102          |
| 0.1078        | 14.0  | 6132 | 0.4519          | 0.5407           | 0.3727        | 0.4144          |
| 0.1034        | 15.0  | 6570 | 0.4677          | 0.5384           | 0.3712        | 0.413           |


### Framework versions

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