---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
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: 0.5493
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.4035        | 1.0   | 500  | 0.9806          | 0.0    | 0.0    | 0.0    | 0.0       |
| 1.049         | 2.0   | 1000 | 0.7479          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.8222        | 3.0   | 1500 | 0.6804          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.7272        | 4.0   | 2000 | 0.6246          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.6758        | 5.0   | 2500 | 0.5872          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.6367        | 6.0   | 3000 | 0.5728          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.6214        | 7.0   | 3500 | 0.5567          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.6107        | 8.0   | 4000 | 0.5493          | 0.0    | 0.0    | 0.0    | 0.0       |


### Framework versions

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