---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task1-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-task1-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: 0.6887
- Accuracy: 0.618

## 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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 10.3747       | 1.0   | 250  | 1.8894          | 0.19     |
| 2.1263        | 2.0   | 500  | 1.3543          | 0.2      |
| 1.5986        | 3.0   | 750  | 1.2566          | 0.2      |
| 1.43          | 4.0   | 1000 | 1.0943          | 0.374    |
| 1.2409        | 5.0   | 1250 | 0.9063          | 0.506    |
| 1.0295        | 6.0   | 1500 | 0.8092          | 0.552    |
| 0.9365        | 7.0   | 1750 | 0.7702          | 0.552    |
| 0.9121        | 8.0   | 2000 | 0.7411          | 0.59     |
| 0.8275        | 9.0   | 2250 | 0.7289          | 0.588    |
| 0.8063        | 10.0  | 2500 | 0.6968          | 0.61     |
| 0.7903        | 11.0  | 2750 | 0.6868          | 0.616    |
| 0.7674        | 12.0  | 3000 | 0.6887          | 0.618    |


### Framework versions

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