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# speller-t5-4

This model is a fine-tuned version of [sberbank-ai/ruT5-base](https://huggingface.co/sberbank-ai/ruT5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1871
- Rouge1: 17.2619
- Rouge2: 7.5893
- Rougel: 17.5595
- Rougelsum: 17.5595
- Gen Len: 42.25

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 0.9773        | 0.04  | 500   | 0.5651          | 14.7321 | 5.2264 | 14.7863 | 14.8471   | 47.2321 |
| 0.8463        | 0.07  | 1000  | 0.4230          | 16.3628 | 5.6052 | 16.3158 | 16.4325   | 47.9018 |
| 0.6458        | 0.11  | 1500  | 0.3528          | 16.2099 | 5.5195 | 16.2034 | 16.3225   | 47.5179 |
| 0.6147        | 0.14  | 2000  | 0.3269          | 16.313  | 5.7216 | 16.313  | 16.4242   | 47.2232 |
| 0.5102        | 0.18  | 2500  | 0.3012          | 16.6071 | 6.0119 | 16.6239 | 16.5792   | 43.1696 |
| 0.4585        | 0.21  | 3000  | 0.2823          | 16.6295 | 6.0714 | 16.6741 | 16.6071   | 47.25   |
| 0.4801        | 0.25  | 3500  | 0.2748          | 16.8779 | 6.3885 | 16.8779 | 16.8779   | 44.5268 |
| 0.4721        | 0.29  | 4000  | 0.2605          | 17.1947 | 7.4353 | 17.3867 | 17.3867   | 42.7054 |
| 0.4132        | 0.32  | 4500  | 0.2530          | 17.2619 | 7.5605 | 17.5054 | 17.5054   | 42.9286 |
| 0.4255        | 0.36  | 5000  | 0.2495          | 17.1503 | 7.4107 | 17.3363 | 17.3363   | 42.5625 |
| 0.3952        | 0.39  | 5500  | 0.2424          | 17.2619 | 7.4702 | 17.4479 | 17.4479   | 42.5089 |
| 0.3229        | 0.43  | 6000  | 0.2354          | 17.2619 | 7.5605 | 17.5054 | 17.5054   | 44.0268 |
| 0.4474        | 0.47  | 6500  | 0.2310          | 17.2619 | 7.5335 | 17.4545 | 17.4545   | 42.5625 |
| 0.3736        | 0.5   | 7000  | 0.2300          | 17.2619 | 7.5335 | 17.4545 | 17.4545   | 42.4286 |
| 0.332         | 0.54  | 7500  | 0.2133          | 17.2619 | 7.5622 | 17.5085 | 17.5085   | 42.4732 |
| 0.3347        | 0.57  | 8000  | 0.2148          | 17.2619 | 7.5605 | 17.5054 | 17.5054   | 42.5    |
| 0.4257        | 0.61  | 8500  | 0.2093          | 17.2619 | 7.5605 | 17.5054 | 17.5054   | 42.3482 |
| 0.3072        | 0.64  | 9000  | 0.2009          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.3661 |
| 0.3184        | 0.68  | 9500  | 0.2028          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.4464 |
| 0.3013        | 0.72  | 10000 | 0.2083          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.2589 |
| 0.3202        | 0.75  | 10500 | 0.2056          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.4911 |
| 0.2689        | 0.79  | 11000 | 0.2020          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.8304 |
| 0.4168        | 0.82  | 11500 | 0.1962          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.2054 |
| 0.287         | 0.86  | 12000 | 0.1930          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.1875 |
| 0.3515        | 0.9   | 12500 | 0.1899          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.1875 |
| 0.2713        | 0.93  | 13000 | 0.1868          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.3304 |
| 0.2914        | 0.97  | 13500 | 0.1871          | 17.2619 | 7.5893 | 17.5595 | 17.5595   | 42.25   |


### 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-t5-4", "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-t5-4
============


This model is a fine-tuned version of sberbank-ai/ruT5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1871
* Rouge1: 17.2619
* Rouge2: 7.5893
* Rougel: 17.5595
* Rougelsum: 17.5595
* Gen Len: 42.25


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