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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 cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4413
- Rouge1: 22.6804
- Rouge2: 8.3299
- Rougel: 17.9992
- Rougelsum: 20.7342

## 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
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.77          | 1.0   | 240  | 2.7230          | 17.25   | 5.629  | 14.0381 | 15.8959   |
| 3.7586        | 2.0   | 480  | 2.5949          | 19.4577 | 6.9354 | 15.772  | 17.8773   |
| 3.4314        | 3.0   | 720  | 2.5355          | 20.0511 | 7.6417 | 16.0889 | 18.4551   |
| 3.2892        | 4.0   | 960  | 2.4845          | 20.3951 | 7.88   | 16.601  | 19.0048   |
| 3.1954        | 5.0   | 1200 | 2.4612          | 20.1806 | 7.2656 | 16.2658 | 18.6222   |
| 3.1128        | 6.0   | 1440 | 2.4544          | 22.5647 | 8.0899 | 17.8057 | 20.487    |
| 3.103         | 7.0   | 1680 | 2.4498          | 22.7048 | 8.384  | 17.978  | 20.6871   |
| 3.0708        | 8.0   | 1920 | 2.4413          | 22.6804 | 8.3299 | 17.9992 | 20.7342   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "datasets": ["cnn_dailymail"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-amazon-en-es", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "cnn_dailymail", "type": "cnn_dailymail", "args": "3.0.0"}, "metrics": [{"type": "rouge", "value": 22.6804, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer dataset:cnn_dailymail license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #model-index #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 cnn\_dailymail dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4413
* Rouge1: 22.6804
* Rouge2: 8.3299
* Rougel: 17.9992
* Rougelsum: 20.7342


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
* num\_epochs: 8


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+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 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #model-index #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 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #model-index #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 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1