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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
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