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# bart-base-finetuned-amazon-onlyen

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7572
- Rouge1: 17.2662
- Rouge2: 8.7425
- Rougel: 16.5765
- Rougelsum: 16.6844

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.9212        | 1.0   | 771  | 2.8034          | 15.381  | 8.5254  | 15.223  | 15.059    |
| 2.3109        | 2.0   | 1542 | 2.8386          | 19.8947 | 11.0965 | 19.4876 | 19.5366   |
| 1.8973        | 3.0   | 2313 | 2.9258          | 17.7443 | 8.9232  | 17.311  | 17.1796   |
| 1.5421        | 4.0   | 3084 | 3.0696          | 17.8204 | 8.8919  | 17.3889 | 17.205    |
| 1.2391        | 5.0   | 3855 | 3.2609          | 15.9828 | 8.0523  | 15.393  | 15.3808   |
| 0.9736        | 6.0   | 4626 | 3.4080          | 15.7572 | 8.806   | 15.2435 | 15.3036   |
| 0.7824        | 7.0   | 5397 | 3.5537          | 18.4389 | 9.5135  | 17.7836 | 17.8758   |
| 0.6233        | 8.0   | 6168 | 3.6909          | 14.6698 | 6.9584  | 13.9417 | 14.0057   |
| 0.5086        | 9.0   | 6939 | 3.7357          | 16.9465 | 7.7604  | 16.1993 | 16.2963   |
| 0.4412        | 10.0  | 7710 | 3.7572          | 17.2662 | 8.7425  | 16.5765 | 16.6844   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "datasets": ["amazon_reviews_multi"], "metrics": ["rouge"], "model-index": [{"name": "bart-base-finetuned-amazon-onlyen", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "amazon_reviews_multi", "type": "amazon_reviews_multi", "args": "en"}, "metrics": [{"type": "rouge", "value": 17.2662, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer dataset:amazon_reviews_multi license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bart-base-finetuned-amazon-onlyen
=================================


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


* Loss: 3.7572
* Rouge1: 17.2662
* Rouge2: 8.7425
* Rougel: 16.5765
* Rougelsum: 16.6844


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: 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1