---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task2-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-task2-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: 0.2211
- Accuracy: 0.758

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9386        | 1.0   | 250  | 0.5169          | 0.622    |
| 0.6505        | 2.0   | 500  | 0.4347          | 0.672    |
| 0.6135        | 3.0   | 750  | 0.3889          | 0.686    |
| 0.5125        | 4.0   | 1000 | 0.3268          | 0.698    |
| 0.4423        | 5.0   | 1250 | 0.3011          | 0.712    |
| 0.3973        | 6.0   | 1500 | 0.2919          | 0.726    |
| 0.3701        | 7.0   | 1750 | 0.2713          | 0.73     |
| 0.337         | 8.0   | 2000 | 0.2540          | 0.738    |
| 0.326         | 9.0   | 2250 | 0.2502          | 0.744    |
| 0.2946        | 10.0  | 2500 | 0.2383          | 0.744    |
| 0.2866        | 11.0  | 2750 | 0.2309          | 0.75     |
| 0.2789        | 12.0  | 3000 | 0.2304          | 0.754    |
| 0.2701        | 13.0  | 3250 | 0.2260          | 0.762    |
| 0.2612        | 14.0  | 3500 | 0.2226          | 0.76     |
| 0.2576        | 15.0  | 3750 | 0.2211          | 0.758    |


### Framework versions

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