---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: cos801-802-hf-workshop-mt5-small
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: swahili
      split: train
      args: swahili
    metrics:
    - name: Rouge1
      type: rouge
      value: 20.928
---

<!-- 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. -->

# cos801-802-hf-workshop-mt5-small

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: 2.7998
- Rouge1: 20.928
- Rouge2: 6.3239
- Rougel: 17.4455
- Rougelsum: 17.4566

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:---------:|
| 3.844         | 1.0   | 1975 | 2.7998          | 20.928 | 6.3239 | 17.4455 | 17.4566   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1