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# mt5-small-finetuned-14feb-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: 2.4516
- Rouge1: 20.33
- Rouge2: 6.2
- Rougel: 19.9

## 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: 0.000275
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.0401        | 1.0   | 388  | 2.5481          | 16.31  | 4.7    | 16.1   |
| 2.9776        | 2.0   | 776  | 2.4442          | 17.25  | 4.93   | 16.93  |
| 2.7362        | 3.0   | 1164 | 2.4181          | 19.73  | 5.74   | 19.21  |
| 2.5767        | 4.0   | 1552 | 2.4071          | 19.37  | 5.62   | 18.89  |
| 2.4466        | 5.0   | 1940 | 2.3560          | 18.98  | 5.94   | 18.55  |
| 2.3402        | 6.0   | 2328 | 2.3923          | 20.45  | 5.5    | 20.03  |
| 2.2385        | 7.0   | 2716 | 2.3639          | 20.03  | 5.96   | 19.76  |
| 2.1663        | 8.0   | 3104 | 2.3431          | 19.17  | 5.34   | 18.84  |
| 2.0849        | 9.0   | 3492 | 2.4008          | 19.97  | 5.58   | 19.67  |
| 2.0203        | 10.0  | 3880 | 2.3948          | 19.67  | 5.75   | 19.26  |
| 1.9653        | 11.0  | 4268 | 2.3915          | 20.06  | 6.07   | 19.61  |
| 1.9067        | 12.0  | 4656 | 2.4025          | 20.83  | 6.46   | 20.41  |
| 1.8592        | 13.0  | 5044 | 2.4194          | 19.97  | 6.4    | 19.69  |
| 1.8158        | 14.0  | 5432 | 2.4156          | 19.87  | 6.16   | 19.38  |
| 1.7679        | 15.0  | 5820 | 2.4053          | 19.9   | 5.99   | 19.52  |
| 1.748         | 16.0  | 6208 | 2.4156          | 19.68  | 5.81   | 19.28  |
| 1.7198        | 17.0  | 6596 | 2.4306          | 20.0   | 6.26   | 19.63  |
| 1.6959        | 18.0  | 6984 | 2.4499          | 19.1   | 6.19   | 18.82  |
| 1.6769        | 19.0  | 7372 | 2.4536          | 20.62  | 6.3    | 20.15  |
| 1.6682        | 20.0  | 7760 | 2.4516          | 20.33  | 6.2    | 19.9   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-14feb-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-14feb-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: 2.4516
* Rouge1: 20.33
* Rouge2: 6.2
* Rougel: 19.9


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: 0.000275
* 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: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000275
* 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: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 0.000275
* 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: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 0.000275
* 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: 20### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2