---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task3-dataset1
  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. -->

# mt5-small-task3-dataset1

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3494
- Accuracy: 0.156
- Mse: 1.4726
- Log-distance: 0.6559
- S Score: 0.5092

## 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: 5.6e-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 | Accuracy | Mse    | Log-distance | S Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
| 12.3227       | 1.0   | 250  | 3.0911          | 0.126    | 1.6773 | 0.5862       | 0.5608  |
| 3.0171        | 2.0   | 500  | 1.8496          | 0.126    | 1.6805 | 0.5886       | 0.5608  |
| 2.1379        | 3.0   | 750  | 1.4488          | 0.126    | 1.6773 | 0.5862       | 0.5608  |
| 1.7896        | 4.0   | 1000 | 1.4309          | 0.126    | 1.6773 | 0.5862       | 0.5608  |
| 1.6843        | 5.0   | 1250 | 1.3863          | 0.136    | 1.5477 | 0.5660       | 0.5764  |
| 1.6196        | 6.0   | 1500 | 1.3676          | 0.142    | 1.4865 | 0.6943       | 0.4700  |
| 1.5812        | 7.0   | 1750 | 1.3518          | 0.14     | 1.4748 | 0.6894       | 0.4728  |
| 1.5336        | 8.0   | 2000 | 1.3538          | 0.148    | 1.6125 | 0.7828       | 0.4220  |
| 1.5106        | 9.0   | 2250 | 1.3468          | 0.172    | 1.4330 | 0.6204       | 0.5484  |
| 1.486         | 10.0  | 2500 | 1.3519          | 0.16     | 1.4487 | 0.6414       | 0.5268  |
| 1.4524        | 11.0  | 2750 | 1.3465          | 0.156    | 1.3796 | 0.5703       | 0.5720  |
| 1.4614        | 12.0  | 3000 | 1.3494          | 0.162    | 1.4250 | 0.6270       | 0.5316  |
| 1.4525        | 13.0  | 3250 | 1.3589          | 0.146    | 1.4602 | 0.6592       | 0.5068  |
| 1.4379        | 14.0  | 3500 | 1.3505          | 0.154    | 1.4722 | 0.6524       | 0.5128  |
| 1.4397        | 15.0  | 3750 | 1.3494          | 0.156    | 1.4726 | 0.6559       | 0.5092  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0