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# bartpho-word-base

This model is a fine-tuned version of [vinai/bartpho-word-base](https://huggingface.co/vinai/bartpho-word-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1067
- Rouge1: 49.261
- Rouge2: 22.7386
- Rougel: 33.4517
- Rougelsum: 35.6277
- Gen Len: 19.8061

## 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: 2e-05
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.7155        | 1.0   | 309  | 2.1805          | 48.1588 | 21.5414 | 32.4169 | 34.6188   | 19.7453 |
| 2.2951        | 2.0   | 619  | 2.1331          | 48.5623 | 21.8348 | 32.7922 | 34.9789   | 19.7525 |
| 2.1676        | 3.0   | 929  | 2.1193          | 49.2433 | 22.8931 | 33.4674 | 35.738    | 19.7881 |
| 2.057         | 4.0   | 1239 | 2.1210          | 49.2825 | 22.7084 | 33.4667 | 35.5888   | 19.7759 |
| 2.0153        | 4.99  | 1545 | 2.1067          | 49.261  | 22.7386 | 33.4517 | 35.6277   | 19.8061 |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.12.0+cu102
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bartpho-word-base", "results": []}]}
transformers pytorch tensorboard mbart text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bartpho-word-base
=================


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


* Loss: 2.1067
* Rouge1: 49.261
* Rouge2: 22.7386
* Rougel: 33.4517
* Rougelsum: 35.6277
* Gen Len: 19.8061


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: 2e-05
* 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


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.0+cu102
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.0+cu102
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.0+cu102
* Datasets 2.12.0
* Tokenizers 0.13.3