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# wiki_lingua-ar-8-8-5.6e-05-mt5-small-finetuned

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3401
- Rouge1: 0.5417
- Rouge2: 0.0921
- Rougel: 0.5445
- Rougelsum: 0.5404

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.851         | 1.0   | 2499  | 2.5949          | 0.4653 | 0.1378 | 0.4684 | 0.4631    |
| 3.0409        | 2.0   | 4998  | 2.4790          | 0.4825 | 0.1156 | 0.4834 | 0.4798    |
| 2.8824        | 3.0   | 7497  | 2.4273          | 0.5264 | 0.1331 | 0.5307 | 0.522     |
| 2.7853        | 4.0   | 9996  | 2.3945          | 0.4879 | 0.1191 | 0.4871 | 0.4811    |
| 2.7221        | 5.0   | 12495 | 2.3678          | 0.5655 | 0.0981 | 0.5672 | 0.5595    |
| 2.6797        | 6.0   | 14994 | 2.3511          | 0.5002 | 0.1191 | 0.5084 | 0.4968    |
| 2.6516        | 7.0   | 17493 | 2.3409          | 0.5606 | 0.1138 | 0.5631 | 0.5578    |
| 2.6364        | 8.0   | 19992 | 2.3401          | 0.5417 | 0.0921 | 0.5445 | 0.5404    |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "datasets": ["wiki_lingua"], "metrics": ["rouge"], "model-index": [{"name": "wiki_lingua-ar-8-8-5.6e-05-mt5-small-finetuned", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wiki_lingua", "type": "wiki_lingua", "config": "ar", "split": "test", "args": "ar"}, "metrics": [{"type": "rouge", "value": 0.5417, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer dataset:wiki_lingua license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

wiki\_lingua-ar-8-8-5.6e-05-mt5-small-finetuned
===============================================


This model is a fine-tuned version of google/mt5-small on the wiki\_lingua dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3401
* Rouge1: 0.5417
* Rouge2: 0.0921
* Rougel: 0.5445
* Rougelsum: 0.5404


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: 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: 8


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* 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: 8 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #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: 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: 8 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #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: 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: 8### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2