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---
license: cc-by-nc-sa-4.0
base_model: deutsche-telekom/mt5-small-sum-de-en-v1
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-sum-de-en-v1-finetuned-amazon-en-de
  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-sum-de-en-v1-finetuned-amazon-en-de

This model is a fine-tuned version of [deutsche-telekom/mt5-small-sum-de-en-v1](https://huggingface.co/deutsche-telekom/mt5-small-sum-de-en-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5661
- Rouge1: 20.9307
- Rouge2: 12.3388
- Rougel: 20.4694
- Rougelsum: 20.6594

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.3857        | 1.0   | 1041  | 2.5918          | 19.0955 | 10.5762 | 18.6534 | 18.707    |
| 2.3597        | 2.0   | 2082  | 2.5887          | 20.2078 | 11.1543 | 19.5663 | 19.7039   |
| 2.3623        | 3.0   | 3123  | 2.5802          | 20.1696 | 12.0499 | 19.7038 | 19.89     |
| 2.3815        | 4.0   | 4164  | 2.5498          | 19.9131 | 11.5376 | 19.4158 | 19.5746   |
| 2.3735        | 5.0   | 5205  | 2.5559          | 20.5713 | 11.8808 | 19.9335 | 20.1211   |
| 2.3269        | 6.0   | 6246  | 2.5574          | 19.8362 | 11.033  | 19.3193 | 19.5623   |
| 2.2956        | 7.0   | 7287  | 2.5479          | 19.8859 | 11.5389 | 19.4015 | 19.7004   |
| 2.2646        | 8.0   | 8328  | 2.5669          | 20.4666 | 12.2804 | 20.0291 | 20.1897   |
| 2.2618        | 9.0   | 9369  | 2.5703          | 20.9783 | 12.3152 | 20.445  | 20.6735   |
| 2.236         | 10.0  | 10410 | 2.5661          | 20.9307 | 12.3388 | 20.4694 | 20.6594   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1