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# distilbart-cnn-arxiv-pubmed-v3-e12

This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed](https://huggingface.co/theojolliffe/distilbart-cnn-arxiv-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8157
- Rouge1: 56.7429
- Rouge2: 41.0185
- Rougel: 44.1014
- Rougelsum: 54.8121
- 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.5037        | 1.0   | 795  | 1.0815          | 52.4727 | 33.4915 | 35.3774 | 50.1955   | 142.0    |
| 0.8894        | 2.0   | 1590 | 0.9462          | 52.8867 | 34.0406 | 36.5249 | 50.4636   | 141.5741 |
| 0.7037        | 3.0   | 2385 | 0.8841          | 53.7966 | 35.0969 | 38.4158 | 51.3369   | 142.0    |
| 0.4914        | 4.0   | 3180 | 0.8437          | 52.6766 | 34.0573 | 36.8907 | 50.3088   | 142.0    |
| 0.3945        | 5.0   | 3975 | 0.8067          | 54.3147 | 36.2081 | 39.6366 | 52.1494   | 142.0    |
| 0.2799        | 6.0   | 4770 | 0.8403          | 54.2813 | 37.0786 | 39.9196 | 51.9176   | 141.9815 |
| 0.2211        | 7.0   | 5565 | 0.8207          | 53.9403 | 36.517  | 39.0372 | 51.4491   | 141.9815 |
| 0.1795        | 8.0   | 6360 | 0.8014          | 55.6607 | 39.3082 | 41.8295 | 53.4674   | 142.0    |
| 0.1428        | 9.0   | 7155 | 0.8051          | 55.0575 | 38.823  | 41.8849 | 52.9606   | 142.0    |
| 0.1358        | 10.0  | 7950 | 0.8149          | 56.6986 | 41.0    | 43.5207 | 54.6402   | 142.0    |
| 0.1122        | 11.0  | 8745 | 0.8134          | 56.5416 | 40.9495 | 44.2989 | 54.5623   | 142.0    |
| 0.0873        | 12.0  | 9540 | 0.8157          | 56.7429 | 41.0185 | 44.1014 | 54.8121   | 142.0    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "distilbart-cnn-arxiv-pubmed-v3-e12", "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-v3-e12
==================================


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


* Loss: 0.8157
* Rouge1: 56.7429
* Rouge2: 41.0185
* Rougel: 44.1014
* Rougelsum: 54.8121
* 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: 12
* 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: 12
* 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-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: 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: 12
* 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-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: 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: 12
* 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