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# t5-small-paraphrasing-mlm-med-mask-filling-cm0

This model is a fine-tuned version of [gayanin/t5-small-paraphrase-pubmed](https://huggingface.co/gayanin/t5-small-paraphrase-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6697
- Rouge2 Precision: 0.6929
- Rouge2 Recall: 0.4742
- Rouge2 Fmeasure: 0.5443

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.9213        | 1.0   | 13915  | 0.8075          | 0.6708           | 0.4603        | 0.5281          |
| 0.8573        | 2.0   | 27830  | 0.7534          | 0.6802           | 0.4671        | 0.5356          |
| 0.8127        | 3.0   | 41745  | 0.7254          | 0.684            | 0.468         | 0.5373          |
| 0.7809        | 4.0   | 55660  | 0.7071          | 0.6867           | 0.4702        | 0.5397          |
| 0.7651        | 5.0   | 69575  | 0.6939          | 0.6886           | 0.4711        | 0.5409          |
| 0.7598        | 6.0   | 83490  | 0.6849          | 0.6904           | 0.4721        | 0.5422          |
| 0.7429        | 7.0   | 97405  | 0.6778          | 0.6917           | 0.4725        | 0.5427          |
| 0.7438        | 8.0   | 111320 | 0.6731          | 0.6917           | 0.4723        | 0.5426          |
| 0.743         | 9.0   | 125235 | 0.6707          | 0.6935           | 0.4748        | 0.545           |
| 0.7349        | 10.0  | 139150 | 0.6697          | 0.6929           | 0.4742        | 0.5443          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-small-paraphrasing-mlm-med-mask-filling-cm0", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-paraphrasing-mlm-med-mask-filling-cm0
==============================================


This model is a fine-tuned version of gayanin/t5-small-paraphrase-pubmed on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6697
* Rouge2 Precision: 0.6929
* Rouge2 Recall: 0.4742
* Rouge2 Fmeasure: 0.5443


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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1