---
license: apache-2.0
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-clara-med
  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-clara-med

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3080
- Rouge1: 30.493
- Rouge2: 15.6893
- Rougel: 26.8862
- Rougelsum: 26.912

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 190  | 3.2218          | 18.2868 | 7.2715  | 16.1223 | 16.4758   |
| No log        | 2.0   | 380  | 2.5984          | 22.723  | 11.054  | 20.6104 | 20.5809   |
| 7.1737        | 3.0   | 570  | 2.4510          | 29.0855 | 14.5467 | 25.516  | 25.5461   |
| 7.1737        | 4.0   | 760  | 2.3834          | 29.5966 | 14.9256 | 26.0424 | 26.0825   |
| 3.3012        | 5.0   | 950  | 2.3490          | 30.0213 | 15.2307 | 26.3306 | 26.3528   |
| 3.3012        | 6.0   | 1140 | 2.3250          | 30.1084 | 15.1684 | 26.4745 | 26.4574   |
| 3.3012        | 7.0   | 1330 | 2.3139          | 30.5785 | 15.7414 | 26.9835 | 27.0047   |
| 3.0426        | 8.0   | 1520 | 2.3080          | 30.493  | 15.6893 | 26.8862 | 26.912    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1