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# mt5-small-finetuned-new3

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: 2.3994
- Rouge1: 20.61
- Rouge2: 6.06
- Rougel: 20.22

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.7204        | 1.45  | 500  | 2.6053          | 16.92  | 4.91   | 16.76  |
| 3.1289        | 2.9   | 1000 | 2.4878          | 18.01  | 5.24   | 17.83  |
| 2.8862        | 4.35  | 1500 | 2.4109          | 17.48  | 5.07   | 17.11  |
| 2.7669        | 5.8   | 2000 | 2.4006          | 18.57  | 5.26   | 18.22  |
| 2.6433        | 7.25  | 2500 | 2.4017          | 18.77  | 5.68   | 18.56  |
| 2.5514        | 8.7   | 3000 | 2.3917          | 19.38  | 5.9    | 19.11  |
| 2.4947        | 10.14 | 3500 | 2.3994          | 20.61  | 6.06   | 20.22  |
| 2.3995        | 11.59 | 4000 | 2.3608          | 20.13  | 6.5    | 19.78  |
| 2.3798        | 13.04 | 4500 | 2.3251          | 20.03  | 6.24   | 19.72  |
| 2.3029        | 14.49 | 5000 | 2.3387          | 19.69  | 6.13   | 19.44  |
| 2.2563        | 15.94 | 5500 | 2.3372          | 20.17  | 6.35   | 19.77  |
| 2.2109        | 17.39 | 6000 | 2.3410          | 20.58  | 6.36   | 20.1   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-new3", "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-new3
========================


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: 2.3994
* Rouge1: 20.61
* Rouge2: 6.06
* Rougel: 20.22


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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2