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# polish_transliterator_T5

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0705
- Rouge1: 15.1042
- Rouge2: 0.0
- Rougel: 15.1042
- Rougelsum: 15.625
- Gen Len: 4.0938

## 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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.0242        | 1.0   | 572   | 1.8076          | 3.5937  | 0.0    | 3.75    | 3.75      | 1.25    |
| 2.8296        | 2.0   | 1144  | 1.6997          | 4.6875  | 0.0    | 4.6875  | 4.6875    | 0.7031  |
| 2.4707        | 3.0   | 1716  | 1.5717          | 6.0417  | 0.0    | 6.25    | 6.3542    | 1.1719  |
| 2.4367        | 4.0   | 2288  | 1.4617          | 6.4062  | 0.0    | 6.875   | 6.875     | 0.9688  |
| 2.296         | 5.0   | 2860  | 1.3847          | 8.4375  | 0.0    | 8.125   | 8.4375    | 1.3906  |
| 2.0905        | 6.0   | 3432  | 1.3177          | 8.4375  | 0.0    | 8.125   | 8.4375    | 1.9688  |
| 1.8223        | 7.0   | 4004  | 1.2645          | 9.375   | 0.0    | 9.375   | 9.375     | 2.3125  |
| 1.6881        | 8.0   | 4576  | 1.2157          | 10.625  | 0.0    | 10.625  | 10.9375   | 2.7969  |
| 1.6655        | 9.0   | 5148  | 1.1841          | 12.5    | 0.0    | 12.2917 | 12.5      | 3.1562  |
| 1.5736        | 10.0  | 5720  | 1.1582          | 13.4896 | 0.0    | 13.3333 | 13.3333   | 3.25    |
| 1.4754        | 11.0  | 6292  | 1.1382          | 13.4896 | 0.0    | 13.3333 | 13.3333   | 3.6562  |
| 1.4927        | 12.0  | 6864  | 1.1176          | 13.4896 | 0.0    | 13.3333 | 13.3333   | 4.1406  |
| 1.3628        | 13.0  | 7436  | 1.1069          | 13.4896 | 0.0    | 13.3333 | 13.3333   | 4.1719  |
| 1.3288        | 14.0  | 8008  | 1.0968          | 13.4896 | 0.0    | 13.3333 | 13.3333   | 4.2344  |
| 1.313         | 15.0  | 8580  | 1.0889          | 14.7917 | 0.0    | 14.7917 | 15.1042   | 4.2188  |
| 1.3215        | 16.0  | 9152  | 1.0820          | 14.7917 | 0.0    | 14.7917 | 15.1042   | 4.2188  |
| 1.2772        | 17.0  | 9724  | 1.0771          | 14.7917 | 0.0    | 14.7917 | 15.1042   | 4.2188  |
| 1.1895        | 18.0  | 10296 | 1.0735          | 15.1042 | 0.0    | 15.1042 | 15.625    | 4.0938  |
| 1.3394        | 19.0  | 10868 | 1.0712          | 15.1042 | 0.0    | 15.1042 | 15.625    | 4.0938  |
| 1.2656        | 20.0  | 11440 | 1.0705          | 15.1042 | 0.0    | 15.1042 | 15.625    | 4.0938  |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "polish_transliterator_T5", "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 

polish\_transliterator\_T5
==========================


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


* Loss: 1.0705
* Rouge1: 15.1042
* Rouge2: 0.0
* Rougel: 15.1042
* Rougelsum: 15.625
* Gen Len: 4.0938


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: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 3e-06
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3