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# article2KW_test1.1_barthez-orangesum-title_finetuned_for_summerization

This model is a fine-tuned version of [moussaKam/barthez-orangesum-title](https://huggingface.co/moussaKam/barthez-orangesum-title) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0775
- Rouge1: 0.2800
- Rouge2: 0.0762
- Rougel: 0.2806
- Rougelsum: 0.2803

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.6345        | 1.0   | 1996 | 1.3251          | 0.2815 | 0.0739 | 0.2816 | 0.2819    |
| 1.2016        | 2.0   | 3992 | 1.1740          | 0.2836 | 0.0727 | 0.2837 | 0.2838    |
| 1.0307        | 3.0   | 5988 | 1.1094          | 0.2874 | 0.0846 | 0.2879 | 0.2877    |
| 0.923         | 4.0   | 7984 | 1.0775          | 0.2800 | 0.0762 | 0.2806 | 0.2803    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "article2KW_test1.1_barthez-orangesum-title_finetuned_for_summerization", "results": []}]}
transformers pytorch mbart text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #mbart #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

article2KW\_test1.1\_barthez-orangesum-title\_finetuned\_for\_summerization
===========================================================================


This model is a fine-tuned version of moussaKam/barthez-orangesum-title on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0775
* Rouge1: 0.2800
* Rouge2: 0.0762
* Rougel: 0.2806
* Rougelsum: 0.2803


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: 6
* eval\_batch\_size: 6
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0
* Datasets 2.3.2
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0
* Datasets 2.3.2
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #mbart #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0
* Datasets 2.3.2
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #mbart #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0
* Datasets 2.3.2
* Tokenizers 0.11.0