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# summarise

This model is a fine-tuned version of [vinai/bartpho-word-base](https://huggingface.co/vinai/bartpho-word-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2042
- Rouge1: 0.3976
- Rouge2: 0.1671
- Rougel: 0.2789
- Rougelsum: 0.2783
- Gen Len: 19.7789

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 0.99  | 97   | 1.5996          | 0.2912 | 0.1103 | 0.2037 | 0.203     | 15.7121 |
| No log        | 2.0   | 195  | 1.3741          | 0.3885 | 0.1547 | 0.2714 | 0.2714    | 19.7044 |
| No log        | 2.99  | 292  | 1.3240          | 0.3687 | 0.1505 | 0.2624 | 0.2624    | 18.9743 |
| No log        | 4.0   | 390  | 1.2874          | 0.3929 | 0.1611 | 0.2775 | 0.2771    | 19.91   |
| No log        | 4.99  | 487  | 1.3065          | 0.3829 | 0.1552 | 0.2667 | 0.2664    | 19.3059 |
| 2.392         | 6.0   | 585  | 1.2555          | 0.3836 | 0.1549 | 0.2689 | 0.2686    | 19.6452 |
| 2.392         | 6.99  | 682  | 1.2605          | 0.3796 | 0.157  | 0.2665 | 0.2663    | 19.3496 |
| 2.392         | 8.0   | 780  | 1.2517          | 0.3969 | 0.1621 | 0.2787 | 0.2781    | 19.8946 |
| 2.392         | 8.99  | 877  | 1.2349          | 0.3885 | 0.1593 | 0.2713 | 0.2709    | 19.7326 |
| 2.392         | 10.0  | 975  | 1.2197          | 0.3864 | 0.1554 | 0.2701 | 0.2695    | 19.4936 |
| 1.2799        | 10.99 | 1072 | 1.2143          | 0.3805 | 0.1565 | 0.2682 | 0.2675    | 19.5141 |
| 1.2799        | 12.0  | 1170 | 1.2111          | 0.391  | 0.1594 | 0.2729 | 0.2725    | 19.6992 |
| 1.2799        | 12.99 | 1267 | 1.1993          | 0.3849 | 0.1568 | 0.2686 | 0.2681    | 19.6632 |
| 1.2799        | 14.0  | 1365 | 1.2196          | 0.3888 | 0.1587 | 0.2733 | 0.273     | 19.6915 |
| 1.2799        | 14.99 | 1462 | 1.1952          | 0.3947 | 0.1611 | 0.2754 | 0.2747    | 19.8021 |
| 1.2178        | 16.0  | 1560 | 1.1982          | 0.3954 | 0.1652 | 0.2778 | 0.2775    | 19.8689 |
| 1.2178        | 16.99 | 1657 | 1.1988          | 0.3957 | 0.1641 | 0.2765 | 0.276     | 19.7121 |
| 1.2178        | 18.0  | 1755 | 1.2020          | 0.3998 | 0.169  | 0.281  | 0.2806    | 19.7815 |
| 1.2178        | 18.99 | 1852 | 1.1995          | 0.3965 | 0.1662 | 0.2782 | 0.2778    | 19.8226 |
| 1.2178        | 19.9  | 1940 | 1.2042          | 0.3976 | 0.1671 | 0.2789 | 0.2783    | 19.7789 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "summarise", "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 

summarise
=========


This model is a fine-tuned version of vinai/bartpho-word-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2042
* Rouge1: 0.3976
* Rouge2: 0.1671
* Rougel: 0.2789
* Rougelsum: 0.2783
* Gen Len: 19.7789


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: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* 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: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3