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# bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-earlystopping

This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8347
- Rouge1: 53.9049
- Rouge2: 35.5953
- Rougel: 39.788
- Rougelsum: 51.4101
- 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: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 0.31  | 125  | 1.0240          | 52.5632 | 32.977  | 34.672  | 49.9905   | 142.0    |
| No log        | 0.63  | 250  | 1.0056          | 52.5508 | 32.4826 | 34.6851 | 49.835    | 141.6852 |
| No log        | 0.94  | 375  | 0.8609          | 53.0475 | 32.9384 | 35.3322 | 50.272    | 141.6481 |
| 0.8255        | 1.26  | 500  | 0.9022          | 52.2493 | 31.5622 | 33.389  | 49.6612   | 142.0    |
| 0.8255        | 1.57  | 625  | 0.8706          | 53.3568 | 33.2533 | 35.7531 | 50.4568   | 141.8889 |
| 0.8255        | 1.88  | 750  | 0.8186          | 52.7375 | 33.4439 | 37.1094 | 50.5323   | 142.0    |
| 0.8255        | 2.2   | 875  | 0.8041          | 53.4992 | 34.6929 | 37.9614 | 51.091    | 142.0    |
| 0.5295        | 2.51  | 1000 | 0.7907          | 52.6185 | 33.8053 | 37.1725 | 50.4881   | 142.0    |
| 0.5295        | 2.83  | 1125 | 0.7740          | 52.7107 | 33.1023 | 36.0865 | 50.0365   | 142.0    |
| 0.5295        | 3.14  | 1250 | 0.8200          | 52.5607 | 33.7948 | 37.2312 | 50.3345   | 142.0    |
| 0.5295        | 3.45  | 1375 | 0.8188          | 53.9233 | 34.446  | 36.7566 | 51.3135   | 142.0    |
| 0.351         | 3.77  | 1500 | 0.8071          | 53.9096 | 35.5977 | 38.6832 | 51.4986   | 142.0    |
| 0.351         | 4.08  | 1625 | 0.8347          | 53.9049 | 35.5953 | 39.788  | 51.4101   | 142.0    |


### Framework versions

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

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

bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-earlystopping
======================================================


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


* Loss: 0.8347
* Rouge1: 53.9049
* Rouge2: 35.5953
* Rougel: 39.788
* Rougelsum: 51.4101
* 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: 200
* 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: 200
* 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-mit #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: 200
* 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-mit #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: 200
* 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