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# mt5-small-finetuned-amazon-en-de

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the [Amazon reviews multi](https://huggingface.co/datasets/amazon_reviews_multi) dataset. 
It achieves the following results on the evaluation set:
- Loss: 3.2896
- Rouge1: 14.7163
- Rouge2: 6.6341
- Rougel: 14.2052
- Rougelsum: 14.2318

## Model description
the model can summarize texts for english and deutsch 
## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure
the training was done on google colab ( using it's free GPU) 
### 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
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.2925        | 1.0   | 1276  | 3.5751          | 13.6254 | 6.0527 | 13.109  | 13.1438   |
| 4.0677        | 2.0   | 2552  | 3.4031          | 13.5907 | 6.068  | 13.3526 | 13.2471   |
| 3.7458        | 3.0   | 3828  | 3.3434          | 14.7229 | 6.8482 | 14.1443 | 14.2218   |
| 3.5831        | 4.0   | 5104  | 3.3353          | 14.8696 | 6.6371 | 14.1342 | 14.2907   |
| 3.4841        | 5.0   | 6380  | 3.3037          | 14.233  | 6.2318 | 13.9218 | 13.9781   |
| 3.4142        | 6.0   | 7656  | 3.2914          | 13.7344 | 5.9446 | 13.5476 | 13.6362   |
| 3.3587        | 7.0   | 8932  | 3.2959          | 14.2007 | 6.1905 | 13.5255 | 13.5237   |
| 3.3448        | 8.0   | 10208 | 3.2896          | 14.7163 | 6.6341 | 14.2052 | 14.2318   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-amazon-en-de", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-small-finetuned-amazon-en-de
================================


This model is a fine-tuned version of google/mt5-small on the Amazon reviews multi dataset.
It achieves the following results on the evaluation set:


* Loss: 3.2896
* Rouge1: 14.7163
* Rouge2: 6.6341
* Rougel: 14.2052
* Rougelsum: 14.2318


Model description
-----------------


the model can summarize texts for english and deutsch


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


More information needed


Training procedure
------------------


the training was done on google colab ( using it's free GPU)


### 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
* num\_epochs: 8


### Training results



### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### 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
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### 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
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### 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
* num\_epochs: 8### Training results### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1