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# mt5-base-finetuned-ar-sp

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2772
- Rouge-1: 23.01
- Rouge-2: 10.41
- Rouge-l: 20.94
- Gen Len: 19.0
- Bertscore: 71.56

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.1968        | 1.0   | 1352 | 3.5142          | 18.69   | 6.73    | 16.97   | 19.0    | 70.3      |
| 3.6932        | 2.0   | 2704 | 3.3799          | 20.67   | 8.38    | 18.75   | 19.0    | 70.82     |
| 3.5058        | 3.0   | 4056 | 3.3184          | 20.97   | 8.58    | 19.08   | 19.0    | 71.08     |
| 3.3832        | 4.0   | 5408 | 3.2851          | 21.59   | 8.94    | 19.63   | 19.0    | 71.28     |
| 3.2994        | 5.0   | 6760 | 3.2772          | 21.84   | 9.23    | 19.85   | 19.0    | 71.34     |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarization", "arabic", "am", "es", "amharic", "mt5", "Abstractive Summarization", "generated_from_trainer"], "model-index": [{"name": "mt5-base-finetuned-ar-sp", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation summarization arabic am es amharic Abstractive 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 #arabic #am #es #amharic #Abstractive Summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-base-finetuned-ar-sp
========================


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


* Loss: 3.2772
* Rouge-1: 23.01
* Rouge-2: 10.41
* Rouge-l: 20.94
* Gen Len: 19.0
* Bertscore: 71.56


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: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* label\_smoothing\_factor: 0.1


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #arabic #am #es #amharic #Abstractive 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: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #arabic #am #es #amharic #Abstractive 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: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* label\_smoothing\_factor: 0.1### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1