---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-swatf
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: swahili
      split: validation
      args: swahili
    metrics:
    - name: Rouge1
      type: rouge
      value: 9.7053
---

<!-- 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-swatf

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 9.7053
- Rouge2: 1.3021
- Rougel: 8.4306
- Rougelsum: 8.4159
- Gen Len: 683.08

## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0           | 0.8   | 500  | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 1.6   | 1000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 2.4   | 1500 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 3.2   | 2000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 4.0   | 2500 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 4.8   | 3000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 5.6   | 3500 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 6.4   | 4000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 7.2   | 4500 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 8.0   | 5000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 8.8   | 5500 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |
| 0.0           | 9.6   | 6000 | nan             | 9.7053 | 1.3021 | 8.4306 | 8.4159    | 683.08  |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3