---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: EN_mt5-small_10_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-small_10_spider

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4350
- Rouge2 Precision: 0.3068
- Rouge2 Recall: 0.202
- Rouge2 Fmeasure: 0.2177

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 1.0   | 438  | 4.5527          | 0.0024           | 0.001         | 0.0014          |
| 17.6146       | 2.0   | 876  | 1.6584          | 0.0              | 0.0           | 0.0             |
| 2.53          | 3.0   | 1314 | 1.5698          | 0.0              | 0.0           | 0.0             |
| 1.9045        | 4.0   | 1752 | 1.3153          | 0.0206           | 0.0074        | 0.0106          |
| 1.5088        | 5.0   | 2190 | 0.6748          | 0.1009           | 0.056         | 0.0623          |
| 0.8005        | 6.0   | 2628 | 0.5124          | 0.2301           | 0.1513        | 0.1593          |
| 0.5297        | 7.0   | 3066 | 0.4683          | 0.2899           | 0.1903        | 0.2021          |
| 0.4507        | 8.0   | 3504 | 0.4464          | 0.2966           | 0.2016        | 0.2129          |
| 0.4507        | 9.0   | 3942 | 0.4385          | 0.3125           | 0.2065        | 0.2224          |
| 0.4161        | 10.0  | 4380 | 0.4350          | 0.3068           | 0.202         | 0.2177          |


### Framework versions

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