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# bart-mlm-paraphrasing

This model is a fine-tuned version of [gayanin/bart-mlm-pubmed](https://huggingface.co/gayanin/bart-mlm-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4617
- Rouge2 Precision: 0.8361
- Rouge2 Recall: 0.6703
- Rouge2 Fmeasure: 0.7304

## 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: 8
- eval_batch_size: 8
- 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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.4845        | 1.0   | 1325  | 0.4270          | 0.8332           | 0.6701        | 0.7294          |
| 0.3911        | 2.0   | 2650  | 0.4195          | 0.8358           | 0.6713        | 0.7313          |
| 0.328         | 3.0   | 3975  | 0.4119          | 0.8355           | 0.6706        | 0.7304          |
| 0.2783        | 4.0   | 5300  | 0.4160          | 0.8347           | 0.6678        | 0.7284          |
| 0.2397        | 5.0   | 6625  | 0.4329          | 0.8411           | 0.6747        | 0.7351          |
| 0.2155        | 6.0   | 7950  | 0.4389          | 0.8382           | 0.6716        | 0.7321          |
| 0.1888        | 7.0   | 9275  | 0.4432          | 0.838            | 0.6718        | 0.7323          |
| 0.1724        | 8.0   | 10600 | 0.4496          | 0.8381           | 0.6714        | 0.7319          |
| 0.1586        | 9.0   | 11925 | 0.4575          | 0.8359           | 0.6704        | 0.7303          |
| 0.1496        | 10.0  | 13250 | 0.4617          | 0.8361           | 0.6703        | 0.7304          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bart-mlm-paraphrasing", "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 

bart-mlm-paraphrasing
=====================


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


* Loss: 0.4617
* Rouge2 Precision: 0.8361
* Rouge2 Recall: 0.6703
* Rouge2 Fmeasure: 0.7304


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: 8
* eval\_batch\_size: 8
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 8
* eval\_batch\_size: 8
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 8
* eval\_batch\_size: 8
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6