---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task3-dataset4
  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-dataset4

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: 1.5832
- Accuracy: 0.056
- Mse: 6.6919
- Log-distance: 0.6837
- S Score: 0.4844

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
| 10.6622       | 1.0   | 250  | 2.1479          | 0.032    | 7.8307 | 0.8081       | 0.4244  |
| 3.1421        | 2.0   | 500  | 1.8253          | 0.044    | 5.7385 | 0.6844       | 0.4892  |
| 2.3451        | 3.0   | 750  | 1.6174          | 0.04     | 5.5959 | 0.6980       | 0.4832  |
| 2.0073        | 4.0   | 1000 | 1.5994          | 0.046    | 6.2422 | 0.6708       | 0.4940  |
| 1.8357        | 5.0   | 1250 | 1.5867          | 0.05     | 6.2493 | 0.6727       | 0.4936  |
| 1.7782        | 6.0   | 1500 | 1.5800          | 0.048    | 6.0314 | 0.6621       | 0.4980  |
| 1.7333        | 7.0   | 1750 | 1.5733          | 0.056    | 6.8849 | 0.6908       | 0.4816  |
| 1.7219        | 8.0   | 2000 | 1.6012          | 0.056    | 6.7969 | 0.6872       | 0.4828  |
| 1.6886        | 9.0   | 2250 | 1.5849          | 0.038    | 6.1512 | 0.6683       | 0.4976  |
| 1.6804        | 10.0  | 2500 | 1.5832          | 0.056    | 6.6919 | 0.6837       | 0.4844  |


### Framework versions

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