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# mt5-small-finetuned-bn_new

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9959
- Rouge1: {'precision': 15.65978835978838, 'recall': 10.193726027059379, 'fmeasure': 12.287113383501408}
- Rougel: {'precision': 14.951058201058215, 'recall': 9.73072853072855, 'fmeasure': 11.728911853731251}

## 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: 5.6e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1                                                                                         | Rougel                                                                                        |
|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|
| 8.555         | 1.0   | 253  | 2.9959          | {'precision': 15.65978835978838, 'recall': 10.193726027059379, 'fmeasure': 12.287113383501408} | {'precision': 14.951058201058215, 'recall': 9.73072853072855, 'fmeasure': 11.728911853731251} |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0+cpu
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-bn_new", "results": []}]}
transformers pytorch mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-small-finetuned-bn\_new
===========================


This model is a fine-tuned version of google/mt5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.9959
* Rouge1: {'precision': 15.65978835978838, 'recall': 10.193726027059379, 'fmeasure': 12.287113383501408}
* Rougel: {'precision': 14.951058201058215, 'recall': 9.73072853072855, 'fmeasure': 11.728911853731251}


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: 5.6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0+cpu
* Datasets 2.10.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0+cpu
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 5.6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0+cpu
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 5.6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0+cpu
* Datasets 2.10.1
* Tokenizers 0.12.1