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# AraT5-base-title-generation-finetuned-ar-xlsum

This model is a fine-tuned version of [UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8120
- Rouge-1: 23.29
- Rouge-2: 8.44
- Rouge-l: 20.74
- Gen Len: 18.16
- Bertscore: 70.88

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 8
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 6.1002        | 1.0   | 5111  | 5.2917          | 18.95   | 5.84    | 17.01   | 17.9    | 68.69     |
| 5.4427        | 2.0   | 10222 | 5.0877          | 20.61   | 6.73    | 18.58   | 17.14   | 69.69     |
| 5.1876        | 3.0   | 15333 | 4.9631          | 21.27   | 7.17    | 19.09   | 17.69   | 69.82     |
| 5.0256        | 4.0   | 20444 | 4.8984          | 21.7    | 7.53    | 19.55   | 17.56   | 70.18     |
| 4.9104        | 5.0   | 25555 | 4.8538          | 22.23   | 7.54    | 19.79   | 17.6    | 70.33     |
| 4.8251        | 6.0   | 30666 | 4.8309          | 22.35   | 7.6     | 19.96   | 17.64   | 70.51     |
| 4.7666        | 7.0   | 35777 | 4.8168          | 22.45   | 7.81    | 20.15   | 17.47   | 70.61     |
| 4.7275        | 8.0   | 40888 | 4.8120          | 22.67   | 7.83    | 20.34   | 17.56   | 70.66     |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["summarization", "generated_from_trainer"], "datasets": ["wiki_lingua"], "model-index": [{"name": "AraT5-base-title-generation-finetuned-ar-xlsum", "results": []}]}
transformers pytorch t5 text2text-generation summarization generated_from_trainer dataset:wiki_lingua autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

AraT5-base-title-generation-finetuned-ar-xlsum
==============================================


This model is a fine-tuned version of UBC-NLP/AraT5-base-title-generation on the wiki\_lingua dataset.
It achieves the following results on the evaluation set:


* Loss: 4.8120
* Rouge-1: 23.29
* Rouge-2: 8.44
* Rouge-l: 20.74
* Gen Len: 18.16
* Bertscore: 70.88


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: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 8
* label\_smoothing\_factor: 0.1


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 8
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 8
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 8
* label\_smoothing\_factor: 0.1### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1