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-text-sum-3
  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-text-sum-3

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: 2.3392
- Rouge1: 21.71
- Rouge2: 6.65
- Rougel: 21.31

## 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: 10
- eval_batch_size: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.6563        | 1.61  | 500  | 2.5975          | 16.78  | 5.15   | 16.64  |
| 3.1112        | 3.22  | 1000 | 2.4856          | 17.05  | 5.31   | 16.8   |
| 2.876         | 4.82  | 1500 | 2.4217          | 18.1   | 5.36   | 17.85  |
| 2.7557        | 6.43  | 2000 | 2.4423          | 18.65  | 5.76   | 18.27  |
| 2.6327        | 8.04  | 2500 | 2.4024          | 19.44  | 6.02   | 19.16  |
| 2.5444        | 9.65  | 3000 | 2.3581          | 18.76  | 5.58   | 18.4   |
| 2.4373        | 11.25 | 3500 | 2.3654          | 19.87  | 6.48   | 19.43  |
| 2.4058        | 12.86 | 4000 | 2.3767          | 19.87  | 5.96   | 19.43  |
| 2.3404        | 14.47 | 4500 | 2.3602          | 20.01  | 5.94   | 19.64  |
| 2.2882        | 16.08 | 5000 | 2.3392          | 21.71  | 6.65   | 21.31  |
| 2.2263        | 17.68 | 5500 | 2.3520          | 20.31  | 6.3    | 20.04  |
| 2.1948        | 19.29 | 6000 | 2.3699          | 21.2   | 6.84   | 20.81  |
| 2.154         | 20.9  | 6500 | 2.3472          | 20.39  | 5.82   | 19.94  |
| 2.1218        | 22.51 | 7000 | 2.3679          | 20.07  | 6.38   | 19.69  |
| 2.073         | 24.12 | 7500 | 2.3457          | 19.7   | 5.8    | 19.2   |


### Framework versions

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