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# distilbart-xsum-6-6-finetuned-bbc-news

This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2624
- Rouge1: 62.1927
- Rouge2: 54.4754
- Rougel: 55.868
- Rougelsum: 60.9345

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.4213        | 1.0   | 445  | 0.2005          | 59.4886 | 51.7791 | 53.5126 | 58.3405   |
| 0.1355        | 2.0   | 890  | 0.1887          | 61.7474 | 54.2823 | 55.7324 | 60.5787   |
| 0.0891        | 3.0   | 1335 | 0.1932          | 61.1312 | 53.103  | 54.6992 | 59.8923   |
| 0.0571        | 4.0   | 1780 | 0.2141          | 60.8797 | 52.6195 | 54.4402 | 59.5298   |
| 0.0375        | 5.0   | 2225 | 0.2318          | 61.7875 | 53.8753 | 55.5068 | 60.5448   |
| 0.0251        | 6.0   | 2670 | 0.2484          | 62.3535 | 54.6029 | 56.2804 | 61.031    |
| 0.0175        | 7.0   | 3115 | 0.2542          | 61.6351 | 53.8248 | 55.6399 | 60.3765   |
| 0.0133        | 8.0   | 3560 | 0.2624          | 62.1927 | 54.4754 | 55.868  | 60.9345   |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarisation", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "distilbart-xsum-6-6-finetuned-bbc-news", "results": []}]}
transformers pytorch tensorboard bart text2text-generation summarisation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarisation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbart-xsum-6-6-finetuned-bbc-news
======================================


This model is a fine-tuned version of sshleifer/distilbart-xsum-6-6 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2624
* Rouge1: 62.1927
* Rouge2: 54.4754
* Rougel: 55.868
* Rougelsum: 60.9345


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: 4
* eval\_batch\_size: 4
* 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 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarisation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarisation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1