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# mt5-small-text-sum-11

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: 2.3761
- Rouge1: 20.13
- Rouge2: 6.41
- Rougel: 19.84

## 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: 0.0001
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.558         | 1.45  | 500  | 2.6110          | 16.89  | 4.81   | 16.86  |
| 3.1188        | 2.9   | 1000 | 2.5397          | 17.58  | 5.27   | 17.4   |
| 2.8995        | 4.35  | 1500 | 2.4761          | 18.14  | 5.11   | 17.9   |
| 2.7608        | 5.8   | 2000 | 2.4130          | 18.52  | 4.95   | 18.15  |
| 2.644         | 7.25  | 2500 | 2.4375          | 18.82  | 5.25   | 18.51  |
| 2.5836        | 8.7   | 3000 | 2.4034          | 19.18  | 5.54   | 18.89  |
| 2.4949        | 10.14 | 3500 | 2.3703          | 19.4   | 5.84   | 18.98  |
| 2.4081        | 11.59 | 4000 | 2.3847          | 19.93  | 6.13   | 19.56  |
| 2.358         | 13.04 | 4500 | 2.3528          | 19.98  | 5.84   | 19.62  |
| 2.2951        | 14.49 | 5000 | 2.3611          | 20.46  | 6.11   | 20.06  |
| 2.2582        | 15.94 | 5500 | 2.3607          | 19.98  | 5.53   | 19.57  |
| 2.2157        | 17.39 | 6000 | 2.3763          | 19.69  | 5.61   | 19.43  |
| 2.1741        | 18.84 | 6500 | 2.3557          | 20.42  | 6.11   | 20.03  |
| 2.1302        | 20.29 | 7000 | 2.3623          | 19.44  | 5.53   | 18.99  |
| 2.1018        | 21.74 | 7500 | 2.3761          | 20.13  | 6.41   | 19.84  |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-text-sum-11", "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-text-sum-11
=====================


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


* Loss: 2.3761
* Rouge1: 20.13
* Rouge2: 6.41
* Rougel: 19.84


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: 0.0001
* train\_batch\_size: 9
* eval\_batch\_size: 9
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 9
* eval\_batch\_size: 9
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* 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: 0.0001
* train\_batch\_size: 9
* eval\_batch\_size: 9
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* 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: 0.0001
* train\_batch\_size: 9
* eval\_batch\_size: 9
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2