---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task1-dataset2
  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-dataset2

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: 0.3880
- Accuracy: 0.182

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3254        | 1.0   | 250  | 0.7650          | 0.0      |
| 0.9928        | 2.0   | 500  | 0.6343          | 0.034    |
| 0.725         | 3.0   | 750  | 0.5447          | 0.114    |
| 0.6197        | 4.0   | 1000 | 0.5004          | 0.106    |
| 0.566         | 5.0   | 1250 | 0.4723          | 0.106    |
| 0.5267        | 6.0   | 1500 | 0.4457          | 0.128    |
| 0.4978        | 7.0   | 1750 | 0.4222          | 0.144    |
| 0.4803        | 8.0   | 2000 | 0.4103          | 0.156    |
| 0.4683        | 9.0   | 2250 | 0.3969          | 0.172    |
| 0.4583        | 10.0  | 2500 | 0.3931          | 0.178    |
| 0.4526        | 11.0  | 2750 | 0.3901          | 0.18     |
| 0.4438        | 12.0  | 3000 | 0.3880          | 0.182    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0