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# speller-t5-finetuned

This model is a fine-tuned version of [UrukHan/t5-russian-spell](https://huggingface.co/UrukHan/t5-russian-spell) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0737
- Rouge1: 25.3988
- Rouge2: 11.756
- Rougel: 25.051
- Rougelsum: 25.2041
- Gen Len: 41.3929

## 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: 5e-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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.1861        | 0.07  | 1000  | 0.1074          | 24.351  | 9.9107  | 24.0512 | 24.1443   | 41.4375 |
| 0.1629        | 0.14  | 2000  | 0.0918          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3839 |
| 0.1545        | 0.21  | 3000  | 0.0898          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.2857 |
| 0.1507        | 0.29  | 4000  | 0.0860          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3571 |
| 0.1472        | 0.36  | 5000  | 0.0823          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3661 |
| 0.1417        | 0.43  | 6000  | 0.0794          | 24.6565 | 10.2976 | 24.265  | 24.4006   | 41.4107 |
| 0.1411        | 0.5   | 7000  | 0.0788          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3482 |
| 0.1395        | 0.57  | 8000  | 0.0786          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3125 |
| 0.1318        | 0.64  | 9000  | 0.0774          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3929 |
| 0.1336        | 0.72  | 10000 | 0.0758          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3839 |
| 0.1332        | 0.79  | 11000 | 0.0743          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3482 |
| 0.1309        | 0.86  | 12000 | 0.0734          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3393 |
| 0.1264        | 0.93  | 13000 | 0.0737          | 25.3988 | 11.756  | 25.051  | 25.2041   | 41.3929 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "speller-t5-finetuned", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

speller-t5-finetuned
====================


This model is a fine-tuned version of UrukHan/t5-russian-spell on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0737
* Rouge1: 25.3988
* Rouge2: 11.756
* Rougel: 25.051
* Rougelsum: 25.2041
* Gen Len: 41.3929


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: 5e-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: 1
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 1
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2