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# distilbart-cnn-arxiv-pubmed-pubmed-earlystopping

This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed](https://huggingface.co/theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8596
- Rouge1: 53.4491
- Rouge2: 35.0041
- Rougel: 37.2742
- Rougelsum: 50.9867
- Gen Len: 142.0

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 0.31  | 125  | 1.3772          | 50.6084 | 30.8075 | 32.6113 | 47.883    | 142.0    |
| No log        | 0.63  | 250  | 1.2423          | 52.1758 | 31.6326 | 32.9448 | 49.8089   | 141.6296 |
| No log        | 0.94  | 375  | 1.1223          | 52.3494 | 32.3508 | 35.3638 | 49.6019   | 142.0    |
| 1.3557        | 1.26  | 500  | 1.1004          | 51.8935 | 32.8506 | 35.521  | 49.6249   | 142.0    |
| 1.3557        | 1.57  | 625  | 1.0600          | 50.8085 | 31.0397 | 34.2021 | 48.2264   | 141.5741 |
| 1.3557        | 1.88  | 750  | 0.9834          | 53.0701 | 34.0699 | 36.4029 | 51.043    | 142.0    |
| 1.3557        | 2.2   | 875  | 0.9554          | 53.4385 | 34.2976 | 36.8142 | 51.1262   | 141.9444 |
| 0.868         | 2.51  | 1000 | 0.9256          | 52.2123 | 32.7568 | 34.5883 | 49.8566   | 142.0    |
| 0.868         | 2.83  | 1125 | 0.8944          | 53.8062 | 34.6687 | 36.9645 | 51.5162   | 142.0    |
| 0.868         | 3.14  | 1250 | 0.9290          | 53.1356 | 34.1301 | 37.7713 | 50.762    | 141.9074 |
| 0.868         | 3.45  | 1375 | 0.9017          | 53.4455 | 35.0572 | 37.3033 | 50.9773   | 142.0    |
| 0.6252        | 3.77  | 1500 | 0.8519          | 53.9228 | 35.5575 | 38.9119 | 51.5202   | 142.0    |
| 0.6252        | 4.08  | 1625 | 0.8991          | 54.4223 | 36.3072 | 38.5771 | 51.9874   | 141.9074 |
| 0.6252        | 4.4   | 1750 | 0.8857          | 53.4105 | 35.348  | 37.5814 | 50.8842   | 142.0    |
| 0.6252        | 4.71  | 1875 | 0.8596          | 53.4491 | 35.0041 | 37.2742 | 50.9867   | 142.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "distilbart-cnn-arxiv-pubmed-pubmed-earlystopping", "results": []}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbart-cnn-arxiv-pubmed-pubmed-earlystopping
================================================


This model is a fine-tuned version of theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8596
* Rouge1: 53.4491
* Rouge2: 35.0041
* Rougel: 37.2742
* Rougelsum: 50.9867
* Gen Len: 142.0


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: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1