---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task2-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-task2-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: 0.4462
- Accuracy: 0.32

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.6376        | 1.0   | 250  | 1.2577          | 0.004    |
| 1.6709        | 2.0   | 500  | 0.8265          | 0.088    |
| 1.0413        | 3.0   | 750  | 0.6782          | 0.144    |
| 0.8324        | 4.0   | 1000 | 0.5901          | 0.222    |
| 0.7187        | 5.0   | 1250 | 0.5476          | 0.246    |
| 0.6556        | 6.0   | 1500 | 0.5215          | 0.276    |
| 0.6089        | 7.0   | 1750 | 0.5028          | 0.274    |
| 0.5736        | 8.0   | 2000 | 0.4930          | 0.304    |
| 0.5385        | 9.0   | 2250 | 0.4695          | 0.296    |
| 0.5195        | 10.0  | 2500 | 0.4650          | 0.304    |
| 0.5073        | 11.0  | 2750 | 0.4571          | 0.304    |
| 0.4895        | 12.0  | 3000 | 0.4491          | 0.306    |
| 0.4836        | 13.0  | 3250 | 0.4495          | 0.316    |
| 0.4745        | 14.0  | 3500 | 0.4460          | 0.318    |
| 0.4736        | 15.0  | 3750 | 0.4462          | 0.32     |


### Framework versions

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