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# bart-cnn-pubmed-arxiv-v3-e16

This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9340
- Rouge1: 57.6388
- Rouge2: 44.834
- Rougel: 47.5043
- Rougelsum: 56.1122
- 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2407        | 1.0   | 795   | 0.9270          | 53.3842 | 33.8559 | 35.7393 | 50.6907   | 142.0   |
| 0.704         | 2.0   | 1590  | 0.8092          | 53.2159 | 35.0209 | 37.8641 | 50.9514   | 141.963 |
| 0.5277        | 3.0   | 2385  | 0.7588          | 52.7709 | 34.2453 | 36.6319 | 50.1137   | 142.0   |
| 0.3449        | 4.0   | 3180  | 0.7617          | 52.0249 | 34.5679 | 37.3669 | 49.7643   | 142.0   |
| 0.2668        | 5.0   | 3975  | 0.7575          | 54.3131 | 35.3985 | 38.9242 | 51.5667   | 142.0   |
| 0.1756        | 6.0   | 4770  | 0.8161          | 53.6214 | 36.4376 | 39.1745 | 51.3685   | 142.0   |
| 0.1326        | 7.0   | 5565  | 0.7848          | 55.7549 | 38.8517 | 42.0106 | 53.4243   | 142.0   |
| 0.1051        | 8.0   | 6360  | 0.7912          | 55.2709 | 39.952  | 42.7398 | 53.6479   | 142.0   |
| 0.0781        | 9.0   | 7155  | 0.8491          | 55.5698 | 40.0599 | 42.9521 | 53.6734   | 142.0   |
| 0.0685        | 10.0  | 7950  | 0.8684          | 55.1142 | 40.3136 | 43.699  | 53.5463   | 142.0   |
| 0.0494        | 11.0  | 8745  | 0.8886          | 57.7988 | 43.6659 | 46.0913 | 56.3383   | 142.0   |
| 0.0338        | 12.0  | 9540  | 0.8827          | 57.0166 | 42.7553 | 46.2344 | 55.2893   | 142.0   |
| 0.0296        | 13.0  | 10335 | 0.9111          | 56.7741 | 42.6116 | 45.1692 | 55.2065   | 142.0   |
| 0.0228        | 14.0  | 11130 | 0.9209          | 56.635  | 43.2461 | 46.314  | 55.049    | 142.0   |
| 0.0189        | 15.0  | 11925 | 0.9193          | 56.4404 | 43.4216 | 46.279  | 55.1403   | 142.0   |
| 0.0152        | 16.0  | 12720 | 0.9340          | 57.6388 | 44.834  | 47.5043 | 56.1122   | 142.0   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-cnn-pubmed-arxiv-v3-e16", "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-v3-e16
============================


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


* Loss: 0.9340
* Rouge1: 57.6388
* Rouge2: 44.834
* Rougel: 47.5043
* Rougelsum: 56.1122
* 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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* 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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* 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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1