---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-13f-reports
  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-finetuned-13f-reports

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5998
- Rouge1: 0.6865
- Rouge2: 0.6132
- Rougel: 0.6746
- Rougelsum: 0.675

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6234        | 1.0   | 126  | 1.1515          | 0.5933 | 0.497  | 0.5686 | 0.5688    |
| 1.5259        | 2.0   | 252  | 0.8439          | 0.6516 | 0.5674 | 0.6349 | 0.6357    |
| 1.2123        | 3.0   | 378  | 0.7462          | 0.661  | 0.5832 | 0.6474 | 0.6478    |
| 0.9923        | 4.0   | 504  | 0.6930          | 0.6674 | 0.5869 | 0.6534 | 0.6544    |
| 0.8811        | 5.0   | 630  | 0.6358          | 0.6747 | 0.595  | 0.662  | 0.6619    |
| 0.7831        | 6.0   | 756  | 0.6148          | 0.686  | 0.6105 | 0.6739 | 0.6741    |
| 0.7908        | 7.0   | 882  | 0.6011          | 0.6871 | 0.6132 | 0.6752 | 0.6755    |
| 0.7525        | 8.0   | 1008 | 0.5998          | 0.6865 | 0.6132 | 0.6746 | 0.675     |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0