---
license: apache-2.0
tags:
- summarization
datasets:
- philschmid/prompted-germanquad
metrics:
- rouge
model-index:
- name: mt5-small-prompted-germanquad-1
  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-prompted-germanquad-1

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: 1.6835
- Rouge1: 27.7309
- Rouge2: 18.7311
- Rougel: 27.4704
- Rougelsum: 27.4818

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3795        | 1.0   | 17496  | 2.0693          | 15.8652 | 9.2569  | 15.6237 | 15.6142   |
| 2.3582        | 2.0   | 34992  | 1.9057          | 21.9348 | 14.0057 | 21.6769 | 21.6825   |
| 2.1809        | 3.0   | 52488  | 1.8143          | 24.3401 | 16.0354 | 24.0862 | 24.0914   |
| 2.0721        | 4.0   | 69984  | 1.7563          | 25.8672 | 17.2442 | 25.5854 | 25.6051   |
| 2.0004        | 5.0   | 87480  | 1.7152          | 27.0275 | 18.0548 | 26.7561 | 26.7685   |
| 1.9531        | 6.0   | 104976 | 1.6939          | 27.4702 | 18.5156 | 27.2027 | 27.2107   |
| 1.9218        | 7.0   | 122472 | 1.6835          | 27.7309 | 18.7311 | 27.4704 | 27.4818   |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.1+cu102
- Datasets 1.16.1
- Tokenizers 0.10.3