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# mt5-small-finetuned-25feb-3

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: 2.3532
- Rouge1: 20.83
- Rouge2: 6.54
- Rougel: 20.4

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 5.3088        | 1.45  | 500  | 2.6216          | 17.35  | 5.18   | 17.14  |
| 3.2982        | 2.9   | 1000 | 2.5396          | 17.76  | 5.55   | 17.53  |
| 2.9211        | 4.35  | 1500 | 2.4802          | 18.72  | 5.62   | 18.47  |
| 2.8162        | 5.8   | 2000 | 2.4158          | 18.16  | 5.26   | 17.7   |
| 2.6661        | 7.25  | 2500 | 2.4387          | 18.59  | 5.38   | 18.21  |
| 2.6102        | 8.7   | 3000 | 2.4044          | 19.54  | 5.63   | 19.16  |
| 2.5043        | 10.14 | 3500 | 2.3738          | 19.65  | 5.79   | 19.16  |
| 2.4598        | 11.59 | 4000 | 2.3805          | 19.86  | 6.29   | 19.43  |
| 2.3807        | 13.04 | 4500 | 2.3590          | 20.13  | 5.91   | 19.62  |
| 2.3461        | 14.49 | 5000 | 2.3611          | 20.73  | 6.28   | 20.31  |
| 2.3024        | 15.94 | 5500 | 2.3571          | 20.64  | 6.12   | 20.25  |
| 2.2704        | 17.39 | 6000 | 2.3723          | 19.71  | 5.95   | 19.35  |
| 2.2356        | 18.84 | 6500 | 2.3532          | 20.83  | 6.54   | 20.4   |
| 2.2019        | 20.29 | 7000 | 2.3597          | 19.67  | 5.91   | 19.28  |
| 2.1646        | 21.74 | 7500 | 2.3733          | 20.63  | 6.53   | 20.24  |
| 2.1511        | 23.19 | 8000 | 2.3534          | 20.63  | 6.22   | 20.22  |
| 2.128         | 24.64 | 8500 | 2.3552          | 20.12  | 5.92   | 19.77  |
| 2.0933        | 26.09 | 9000 | 2.3587          | 20.53  | 5.88   | 20.06  |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-25feb-3", "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-25feb-3
===========================


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: 2.3532
* Rouge1: 20.83
* Rouge2: 6.54
* Rougel: 20.4


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: 30


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* 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: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* 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: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* 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: 30### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2