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# mt5-small-finetuned-amazon-en-es

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: 3.0132
- Rouge1: 16.4719
- Rouge2: 7.9366
- Rougel: 16.2123
- Rougelsum: 16.2853

## 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
- distributed_type: multi-GPU
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.9249        | 1.0   | 1209 | 3.1904          | 15.8207 | 8.0555 | 15.4584 | 15.648    |
| 3.5688        | 2.0   | 2418 | 3.0812          | 16.3271 | 8.1479 | 15.9001 | 16.0134   |
| 3.3905        | 3.0   | 3627 | 3.0442          | 15.9864 | 7.295  | 15.4247 | 15.5848   |
| 3.2728        | 4.0   | 4836 | 3.0304          | 16.2893 | 7.5851 | 15.9494 | 16.0117   |
| 3.1958        | 5.0   | 6045 | 3.0169          | 15.4888 | 7.4495 | 15.2244 | 15.2326   |
| 3.1359        | 6.0   | 7254 | 3.0158          | 16.3866 | 8.2218 | 16.0625 | 16.0953   |
| 3.1059        | 7.0   | 8463 | 3.0075          | 15.9134 | 7.8387 | 15.626  | 15.6499   |
| 3.0852        | 8.0   | 9672 | 3.0132          | 16.4719 | 7.9366 | 16.2123 | 16.2853   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-amazon-en-es", "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-es
================================


This model is a fine-tuned version of google/mt5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 3.0132
* Rouge1: 16.4719
* Rouge2: 7.9366
* Rougel: 16.2123
* Rougelsum: 16.2853


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
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.2
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
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.2