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# bart-cnn-pubmed-arxiv-pubmed-v3-e10

This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8410
- Rouge1: 56.5123
- Rouge2: 41.1641
- Rougel: 43.4495
- Rougelsum: 54.544
- Gen Len: 141.6667

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.254         | 1.0   | 795  | 0.9244          | 52.4478 | 32.5958 | 34.8756 | 49.8059   | 142.0    |
| 0.6985        | 2.0   | 1590 | 0.8156          | 52.4786 | 33.2296 | 35.5063 | 49.737    | 141.7963 |
| 0.5252        | 3.0   | 2385 | 0.7821          | 52.0494 | 32.953  | 36.5502 | 49.7292   | 142.0    |
| 0.3389        | 4.0   | 3180 | 0.7422          | 53.5408 | 36.2206 | 39.8389 | 51.6693   | 142.0    |
| 0.26          | 5.0   | 3975 | 0.7670          | 54.4279 | 36.5972 | 40.255  | 52.0877   | 142.0    |
| 0.1678        | 6.0   | 4770 | 0.8106          | 54.6811 | 37.8329 | 40.8512 | 52.3482   | 141.963  |
| 0.1243        | 7.0   | 5565 | 0.7926          | 54.5081 | 37.9596 | 41.912  | 52.5097   | 142.0    |
| 0.0967        | 8.0   | 6360 | 0.8079          | 56.0795 | 40.0954 | 43.7055 | 54.2041   | 142.0    |
| 0.0709        | 9.0   | 7155 | 0.8390          | 55.5257 | 38.5546 | 42.1562 | 53.5524   | 141.963  |
| 0.0691        | 10.0  | 7950 | 0.8410          | 56.5123 | 41.1641 | 43.4495 | 54.544    | 141.6667 |


### 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-pubmed-v3-e10", "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-v3-e10
===================================


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


* Loss: 0.8410
* Rouge1: 56.5123
* Rouge2: 41.1641
* Rougel: 43.4495
* Rougelsum: 54.544
* Gen Len: 141.6667


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: 10
* 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: 10
* 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: 10
* 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: 10
* 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