---
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: 0.6492
- Accuracy: 0.626

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 10.2312       | 1.0   | 250  | 2.1246          | 0.194    |
| 2.2998        | 2.0   | 500  | 1.4171          | 0.194    |
| 1.6645        | 3.0   | 750  | 1.2718          | 0.206    |
| 1.4575        | 4.0   | 1000 | 1.1549          | 0.258    |
| 1.3335        | 5.0   | 1250 | 1.0267          | 0.432    |
| 1.1696        | 6.0   | 1500 | 0.8811          | 0.5      |
| 0.9974        | 7.0   | 1750 | 0.7960          | 0.532    |
| 0.9162        | 8.0   | 2000 | 0.7576          | 0.556    |
| 0.8463        | 9.0   | 2250 | 0.7342          | 0.588    |
| 0.8078        | 10.0  | 2500 | 0.6856          | 0.606    |
| 0.7751        | 11.0  | 2750 | 0.6655          | 0.612    |
| 0.7533        | 12.0  | 3000 | 0.6645          | 0.622    |
| 0.7337        | 13.0  | 3250 | 0.6625          | 0.62     |
| 0.7154        | 14.0  | 3500 | 0.6640          | 0.624    |
| 0.7038        | 15.0  | 3750 | 0.6492          | 0.626    |


### Framework versions

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