---
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: test
      args: swahili
    metrics:
    - name: Rouge1
      type: rouge
      value: 9.6904
---

<!-- 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: 9.6904
- Rouge2: 1.3302
- Rougel: 8.4948
- Rougelsum: 8.497
- Gen Len: 685.8156

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| No log        | 1.0   | 188  | nan             | 9.6904 | 1.3302 | 8.4948 | 8.497     | 685.8156 |
| No log        | 2.0   | 376  | nan             | 9.6904 | 1.3302 | 8.4948 | 8.497     | 685.8156 |
| 0.0           | 3.0   | 564  | nan             | 9.6904 | 1.3302 | 8.4948 | 8.497     | 685.8156 |
| 0.0           | 4.0   | 752  | nan             | 9.6904 | 1.3302 | 8.4948 | 8.497     | 685.8156 |
| 0.0           | 5.0   | 940  | nan             | 9.6904 | 1.3302 | 8.4948 | 8.497     | 685.8156 |


### Framework versions

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