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# bart-large-finetuned-pubmed

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the pub_med_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8135
- Rouge1: 10.946
- Rouge2: 5.0933
- Rougel: 9.5608
- Rougelsum: 10.4259
- Gen Len: 19.0495

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
| 2.0861        | 1.0   | 4000  | 1.8909          | 8.7344  | 3.6919 | 7.8804 | 8.3305    | 20.0    |
| 1.8996        | 2.0   | 8000  | 1.8261          | 10.2124 | 4.6212 | 8.9842 | 9.7417    | 17.632  |
| 1.7459        | 3.0   | 12000 | 1.8160          | 9.4933  | 4.4117 | 8.3977 | 9.0758    | 16.4775 |
| 1.6258        | 4.0   | 16000 | 1.8136          | 10.8248 | 5.0335 | 9.4286 | 10.3123   | 18.724  |
| 1.5214        | 5.0   | 20000 | 1.8135          | 10.946  | 5.0933 | 9.5608 | 10.4259   | 19.0495 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["pub_med_summarization_dataset"], "metrics": ["rouge"], "model-index": [{"name": "bart-large-finetuned-pubmed", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "pub_med_summarization_dataset", "type": "pub_med_summarization_dataset", "args": "document"}, "metrics": [{"type": "rouge", "value": 10.946, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer dataset:pub_med_summarization_dataset license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bart-large-finetuned-pubmed
===========================


This model is a fine-tuned version of facebook/bart-large on the pub\_med\_summarization\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 1.8135
* Rouge1: 10.946
* Rouge2: 5.0933
* Rougel: 9.5608
* Rougelsum: 10.4259
* Gen Len: 19.0495


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: 5
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6



### 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: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #license-apache-2.0 #model-index #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: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #license-apache-2.0 #model-index #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: 5
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6