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# pegasus-xsum_summarization

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7876
- Rouge1: 25.7148
- Rouge2: 10.9685
- Rougel: 21.6394
- Rougelsum: 22.3122

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.633         | 1.0   | 50   | 1.8839          | 24.9703 | 9.6517  | 19.9759 | 21.088    |
| 1.3917        | 2.0   | 100  | 1.8565          | 24.4395 | 9.1755  | 19.5702 | 20.5489   |
| 1.2576        | 3.0   | 150  | 1.8361          | 24.8266 | 10.2009 | 20.074  | 21.382    |
| 1.1191        | 4.0   | 200  | 1.8226          | 25.9635 | 11.7704 | 21.7787 | 22.365    |
| 1.1138        | 5.0   | 250  | 1.8239          | 26.7874 | 12.2832 | 22.7792 | 23.4501   |
| 1.0338        | 6.0   | 300  | 1.8094          | 26.3543 | 12.0501 | 22.3172 | 23.1194   |
| 1.0084        | 7.0   | 350  | 1.7923          | 25.5686 | 11.0213 | 21.5288 | 21.8892   |
| 1.0098        | 8.0   | 400  | 1.7876          | 25.7148 | 10.9685 | 21.6394 | 22.3122   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "pegasus-xsum_summarization", "results": []}]}
transformers pytorch pegasus text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

pegasus-xsum\_summarization
===========================


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


* Loss: 1.7876
* Rouge1: 25.7148
* Rouge2: 10.9685
* Rougel: 21.6394
* Rougelsum: 22.3122


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: 8


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* 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: 8 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #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: 8 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #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: 8### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1