
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# mT5_multilingual_XLSum-sinhala-abstaractive-summarization_CNN-dailymail-V2

This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the CNN daily-mail sinhala dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4863
- Rouge1: 19.9769
- Rouge2: 8.04
- Rougel: 19.0307
- Rougelsum: 19.7651

## 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: 0.00056
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 1.8746        | 1.0   | 750  | 1.8262          | 18.9753 | 7.9271 | 18.1349 | 18.7152   |
| 1.4727        | 2.0   | 1500 | 1.8094          | 19.2219 | 7.9749 | 18.4314 | 18.9405   |
| 1.2331        | 3.0   | 2250 | 1.8432          | 20.436  | 7.8378 | 19.584  | 20.1613   |
| 1.0381        | 4.0   | 3000 | 1.8987          | 20.2251 | 7.9593 | 19.1556 | 19.9829   |
| 0.8737        | 5.0   | 3750 | 1.9471          | 20.3262 | 7.8935 | 19.407  | 20.0628   |
| 0.7363        | 6.0   | 4500 | 2.0611          | 20.1551 | 7.5046 | 19.2213 | 19.963    |
| 0.6214        | 7.0   | 5250 | 2.1838          | 19.9045 | 7.6232 | 18.743  | 19.5983   |
| 0.5277        | 8.0   | 6000 | 2.3190          | 20.8581 | 8.1054 | 19.8079 | 20.5414   |
| 0.4576        | 9.0   | 6750 | 2.4091          | 20.028  | 7.7635 | 19.0721 | 19.7053   |
| 0.4099        | 10.0  | 7500 | 2.4863          | 19.9769 | 8.04   | 19.0307 | 19.7651   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mT5_multilingual_XLSum-sinhala-abstaractive-summarization_CNN-dailymail-V2", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mT5\_multilingual\_XLSum-sinhala-abstaractive-summarization\_CNN-dailymail-V2
=============================================================================


This model is a fine-tuned version of csebuetnlp/mT5\_multilingual\_XLSum on the CNN daily-mail sinhala dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4863
* Rouge1: 19.9769
* Rouge2: 8.04
* Rougel: 19.0307
* Rougelsum: 19.7651


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: 0.00056
* 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: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00056
* 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: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00056
* 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: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00056
* 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: 10### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3