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# mt5-small-finetuned-28feb-1

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: 2.3686
- Rouge1: 20.86
- Rouge2: 6.65
- Rougel: 20.57

## 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: 13
- eval_batch_size: 13
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 3.3725        | 2.09  | 500  | 2.5493          | 17.49  | 5.58   | 17.34  |
| 2.9876        | 4.18  | 1000 | 2.4931          | 18.9   | 5.35   | 18.8   |
| 2.7925        | 6.28  | 1500 | 2.4054          | 18.26  | 5.11   | 18.01  |
| 2.6561        | 8.37  | 2000 | 2.3951          | 19.83  | 5.84   | 19.43  |
| 2.5491        | 10.46 | 2500 | 2.3602          | 19.11  | 5.69   | 18.8   |
| 2.4504        | 12.55 | 3000 | 2.3458          | 20.83  | 6.74   | 20.52  |
| 2.3708        | 14.64 | 3500 | 2.3739          | 20.69  | 6.53   | 20.43  |
| 2.3075        | 16.74 | 4000 | 2.3414          | 19.32  | 6.58   | 19.12  |
| 2.2512        | 18.83 | 4500 | 2.3589          | 19.38  | 6.07   | 19.0   |
| 2.1554        | 20.92 | 5000 | 2.3686          | 20.86  | 6.65   | 20.57  |
| 2.1141        | 23.01 | 5500 | 2.3768          | 20.71  | 6.46   | 20.37  |
| 2.0774        | 25.1  | 6000 | 2.3627          | 20.25  | 6.22   | 20.0   |
| 2.0315        | 27.2  | 6500 | 2.3521          | 20.37  | 6.28   | 20.05  |
| 1.9787        | 29.29 | 7000 | 2.3699          | 20.75  | 6.6    | 20.43  |
| 1.9645        | 31.38 | 7500 | 2.3554          | 20.27  | 5.9    | 20.0   |


### 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-28feb-1", "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-28feb-1
===========================


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: 2.3686
* Rouge1: 20.86
* Rouge2: 6.65
* Rougel: 20.57


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: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60


### 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: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60 ### 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: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60 ### 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: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60### Training results### Framework versions


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