transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned
  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

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: 2.3994
- Rouge1: 20.69
- Rouge2: 6.09
- Rougel: 20.15

## 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: 0.0001
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.7204        | 1.45  | 500  | 2.6053          | 16.93  | 4.91   | 16.71  |
| 3.1289        | 2.9   | 1000 | 2.4878          | 18.05  | 5.26   | 17.79  |
| 2.8862        | 4.35  | 1500 | 2.4109          | 17.45  | 5.06   | 17.04  |
| 2.7669        | 5.8   | 2000 | 2.4006          | 18.61  | 5.28   | 18.12  |
| 2.6433        | 7.25  | 2500 | 2.4017          | 18.81  | 5.67   | 18.5   |
| 2.5514        | 8.7   | 3000 | 2.3917          | 19.5   | 5.88   | 19.09  |
| 2.4947        | 10.14 | 3500 | 2.3994          | 20.69  | 6.09   | 20.15  |
| 2.3995        | 11.59 | 4000 | 2.3608          | 20.2   | 6.51   | 19.67  |
| 2.3798        | 13.04 | 4500 | 2.3251          | 20.1   | 6.25   | 19.71  |
| 2.3029        | 14.49 | 5000 | 2.3387          | 19.75  | 6.11   | 19.37  |
| 2.2563        | 15.94 | 5500 | 2.3372          | 20.28  | 6.32   | 19.74  |
| 2.2109        | 17.39 | 6000 | 2.3410          | 20.67  | 6.38   | 20.13  |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
