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# bart-base-finetuned-xsum

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3082
- Rouge1: 13.998
- Rouge2: 8.2042
- Rougel: 13.2682
- Rougelsum: 13.6101
- Gen Len: 20.0

## 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: 0.002
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 50
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 180  | 1.5657          | 13.284  | 6.5156 | 12.5098 | 12.8132   | 20.0    |
| No log        | 2.0   | 360  | 1.0051          | 13.3398 | 6.426  | 12.4508 | 12.9061   | 20.0    |
| 1.9306        | 3.0   | 540  | 0.7440          | 12.8324 | 6.2848 | 11.9985 | 12.4138   | 20.0    |
| 1.9306        | 4.0   | 720  | 0.5412          | 13.2678 | 6.7085 | 12.4631 | 12.9015   | 20.0    |
| 1.9306        | 5.0   | 900  | 0.4288          | 13.4092 | 6.9196 | 12.4719 | 12.9804   | 20.0    |
| 0.625         | 6.0   | 1080 | 0.3653          | 13.8777 | 7.53   | 13.0145 | 13.4782   | 20.0    |
| 0.625         | 7.0   | 1260 | 0.3255          | 14.585  | 8.5087 | 13.8215 | 14.1797   | 20.0    |
| 0.625         | 8.0   | 1440 | 0.3082          | 13.998  | 8.2042 | 13.2682 | 13.6101   | 20.0    |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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

bart-base-finetuned-xsum
========================


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


* Loss: 0.3082
* Rouge1: 13.998
* Rouge2: 8.2042
* Rougel: 13.2682
* Rougelsum: 13.6101
* Gen Len: 20.0


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: 0.002
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 50
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 50
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 50
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 50
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2