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# bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-v3-e12

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: 0.8501
- Rouge1: 56.1453
- Rouge2: 40.018
- Rougel: 43.5586
- Rougelsum: 54.4271
- 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 398  | 0.8670          | 54.4613 | 34.7958 | 36.5841 | 51.9208   | 142.0   |
| 0.8276        | 2.0   | 796  | 0.8061          | 53.5804 | 34.5801 | 37.4643 | 51.1494   | 142.0   |
| 0.5318        | 3.0   | 1194 | 0.8146          | 53.7541 | 34.2446 | 37.5488 | 51.2475   | 142.0   |
| 0.3541        | 4.0   | 1592 | 0.7578          | 53.7645 | 34.874  | 38.3958 | 51.3075   | 142.0   |
| 0.3541        | 5.0   | 1990 | 0.7778          | 55.2787 | 37.5539 | 40.5489 | 52.8514   | 142.0   |
| 0.2386        | 6.0   | 2388 | 0.7810          | 55.2487 | 38.6522 | 41.466  | 53.379    | 142.0   |
| 0.1652        | 7.0   | 2786 | 0.7905          | 54.3618 | 37.4987 | 40.7348 | 52.2938   | 142.0   |
| 0.1152        | 8.0   | 3184 | 0.7934          | 54.4888 | 37.649  | 40.3582 | 52.3451   | 142.0   |
| 0.0942        | 9.0   | 3582 | 0.8220          | 55.5489 | 39.8493 | 42.2318 | 53.727    | 142.0   |
| 0.0942        | 10.0  | 3980 | 0.8331          | 55.7509 | 39.9491 | 43.2336 | 53.9748   | 142.0   |
| 0.0669        | 11.0  | 4378 | 0.8298          | 57.3881 | 42.6588 | 45.4694 | 55.8334   | 142.0   |
| 0.0531        | 12.0  | 4776 | 0.8501          | 56.1453 | 40.018  | 43.5586 | 54.4271   | 142.0   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-v3-e12", "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-v3-e12
===============================================


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: 0.8501
* Rouge1: 56.1453
* Rouge2: 40.018
* Rougel: 43.5586
* Rougelsum: 54.4271
* 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: 12
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 12
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 12
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 12
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1