---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: ML5-fine-tuning-xsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.5714
---

<!-- 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. -->

# ML5-fine-tuning-xsum

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4333
- Rouge1: 0.5714
- Rouge2: 0.0
- Rougel: 0.5714
- Rougelsum: 0.5714

## 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: 0.001
- 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 18.7065       | 1.0   | 7    | 9.6966          | 0.0    | 0.0    | 0.0    | 0.0       |
| 10.3198       | 2.0   | 14   | 7.4333          | 0.5714 | 0.0    | 0.5714 | 0.5714    |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1