---
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: 1.6024
- Accuracy: 0.038
- Mse: 6.4524
- Log-distance: 0.6628
- S Score: 0.4912

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
| 12.4369       | 1.0   | 250  | 2.2550          | 0.038    | 6.7116 | 0.6817       | 0.4748  |
| 3.1387        | 2.0   | 500  | 1.8576          | 0.024    | 5.8813 | 0.7455       | 0.4552  |
| 2.3265        | 3.0   | 750  | 1.6663          | 0.05     | 7.7168 | 0.7232       | 0.4556  |
| 1.9955        | 4.0   | 1000 | 1.6121          | 0.04     | 6.3175 | 0.6614       | 0.4908  |
| 1.8234        | 5.0   | 1250 | 1.6380          | 0.034    | 6.8099 | 0.6780       | 0.4860  |
| 1.7591        | 6.0   | 1500 | 1.5953          | 0.04     | 6.3175 | 0.6614       | 0.4908  |
| 1.7194        | 7.0   | 1750 | 1.5996          | 0.054    | 6.0821 | 0.6559       | 0.4976  |
| 1.6988        | 8.0   | 2000 | 1.5970          | 0.048    | 6.6575 | 0.6618       | 0.4952  |
| 1.6831        | 9.0   | 2250 | 1.6024          | 0.038    | 6.4524 | 0.6628       | 0.4912  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0