---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task2-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-task2-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: 0.5227
- Accuracy: 0.212

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.2329        | 1.0   | 250  | 1.3076          | 0.006    |
| 1.6853        | 2.0   | 500  | 0.8967          | 0.09     |
| 1.123         | 3.0   | 750  | 0.7346          | 0.132    |
| 0.907         | 4.0   | 1000 | 0.6587          | 0.162    |
| 0.7875        | 5.0   | 1250 | 0.6083          | 0.17     |
| 0.7135        | 6.0   | 1500 | 0.5807          | 0.188    |
| 0.675         | 7.0   | 1750 | 0.5566          | 0.196    |
| 0.6403        | 8.0   | 2000 | 0.5427          | 0.206    |
| 0.6229        | 9.0   | 2250 | 0.5354          | 0.208    |
| 0.6046        | 10.0  | 2500 | 0.5329          | 0.212    |
| 0.5974        | 11.0  | 2750 | 0.5237          | 0.212    |
| 0.5875        | 12.0  | 3000 | 0.5227          | 0.212    |


### Framework versions

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