---
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: 0.4838
- Accuracy: 0.224

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.0046        | 1.0   | 250  | 1.3356          | 0.008    |
| 1.8352        | 2.0   | 500  | 0.9395          | 0.082    |
| 1.2215        | 3.0   | 750  | 0.7493          | 0.13     |
| 0.9711        | 4.0   | 1000 | 0.6537          | 0.162    |
| 0.8269        | 5.0   | 1250 | 0.5908          | 0.176    |
| 0.741         | 6.0   | 1500 | 0.5548          | 0.19     |
| 0.6896        | 7.0   | 1750 | 0.5377          | 0.194    |
| 0.651         | 8.0   | 2000 | 0.5198          | 0.21     |
| 0.627         | 9.0   | 2250 | 0.5086          | 0.224    |
| 0.606         | 10.0  | 2500 | 0.5006          | 0.228    |
| 0.5849        | 11.0  | 2750 | 0.4948          | 0.232    |
| 0.5733        | 12.0  | 3000 | 0.4928          | 0.23     |
| 0.5607        | 13.0  | 3250 | 0.4851          | 0.224    |
| 0.5599        | 14.0  | 3500 | 0.4842          | 0.222    |
| 0.5584        | 15.0  | 3750 | 0.4838          | 0.224    |


### Framework versions

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