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-6
  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-6

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: 2.3694
- Rouge1: 20.18
- Rouge2: 6.52
- Rougel: 19.84

## 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: 12
- eval_batch_size: 12
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.4337        | 1.93  | 500  | 2.5989          | 15.94  | 4.85   | 15.78  |
| 3.0621        | 3.86  | 1000 | 2.4750          | 19.09  | 5.95   | 18.82  |
| 2.8411        | 5.79  | 1500 | 2.4011          | 18.39  | 5.69   | 18.22  |
| 2.6947        | 7.72  | 2000 | 2.3851          | 19.27  | 5.79   | 19.01  |
| 2.5872        | 9.65  | 2500 | 2.3918          | 19.09  | 6.02   | 18.81  |
| 2.4996        | 11.58 | 3000 | 2.3689          | 18.84  | 5.84   | 18.46  |
| 2.4192        | 13.51 | 3500 | 2.3604          | 19.89  | 5.97   | 19.5   |
| 2.3524        | 15.44 | 4000 | 2.3694          | 20.18  | 6.52   | 19.84  |
| 2.3012        | 17.37 | 4500 | 2.3637          | 19.24  | 5.51   | 18.9   |
| 2.2408        | 19.31 | 5000 | 2.3374          | 19.78  | 6.27   | 19.43  |
| 2.2004        | 21.24 | 5500 | 2.3400          | 19.74  | 6.06   | 19.37  |
| 2.1631        | 23.17 | 6000 | 2.3584          | 19.95  | 6.08   | 19.53  |
| 2.123         | 25.1  | 6500 | 2.3527          | 19.64  | 5.9    | 19.36  |


### Framework versions

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