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# t5-base-finetuned-es-to-pua

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4986
- Bleu: 1.7461
- Gen Len: 15.8171

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 36   | 3.4870          | 0.0863 | 17.9878 |
| No log        | 2.0   | 72   | 3.0772          | 0.2333 | 17.622  |
| No log        | 3.0   | 108  | 2.7865          | 0.2752 | 16.6829 |
| No log        | 4.0   | 144  | 2.5878          | 0.8782 | 17.9024 |
| No log        | 5.0   | 180  | 2.4639          | 1.584  | 17.1463 |
| No log        | 6.0   | 216  | 2.3559          | 0.9321 | 16.8049 |
| No log        | 7.0   | 252  | 2.2704          | 1.0018 | 17.3902 |
| No log        | 8.0   | 288  | 2.1956          | 1.2549 | 17.0732 |
| No log        | 9.0   | 324  | 2.1307          | 0.9709 | 17.4268 |
| No log        | 10.0  | 360  | 2.0866          | 0.7563 | 17.5    |
| No log        | 11.0  | 396  | 2.0392          | 0.707  | 17.2439 |
| No log        | 12.0  | 432  | 1.9920          | 0.8647 | 16.9756 |
| No log        | 13.0  | 468  | 1.9630          | 0.8724 | 17.8171 |
| 2.7137        | 14.0  | 504  | 1.9244          | 1.0593 | 17.4146 |
| 2.7137        | 15.0  | 540  | 1.9010          | 1.6823 | 17.061  |
| 2.7137        | 16.0  | 576  | 1.8711          | 1.6452 | 16.5732 |
| 2.7137        | 17.0  | 612  | 1.8475          | 1.6622 | 16.8659 |
| 2.7137        | 18.0  | 648  | 1.8265          | 2.2968 | 16.7195 |
| 2.7137        | 19.0  | 684  | 1.8056          | 2.2125 | 16.6098 |
| 2.7137        | 20.0  | 720  | 1.7962          | 2.3889 | 16.3049 |
| 2.7137        | 21.0  | 756  | 1.7778          | 2.341  | 16.3537 |
| 2.7137        | 22.0  | 792  | 1.7626          | 2.3187 | 16.1341 |
| 2.7137        | 23.0  | 828  | 1.7450          | 2.5281 | 16.0732 |
| 2.7137        | 24.0  | 864  | 1.7357          | 2.6768 | 15.9268 |
| 2.7137        | 25.0  | 900  | 1.7177          | 2.3932 | 15.9146 |
| 2.7137        | 26.0  | 936  | 1.7126          | 2.611  | 15.8537 |
| 2.7137        | 27.0  | 972  | 1.7088          | 2.2829 | 15.622  |
| 1.9301        | 28.0  | 1008 | 1.6868          | 2.4441 | 15.8293 |
| 1.9301        | 29.0  | 1044 | 1.6707          | 2.5402 | 16.0976 |
| 1.9301        | 30.0  | 1080 | 1.6790          | 2.0723 | 15.561  |
| 1.9301        | 31.0  | 1116 | 1.6600          | 1.4278 | 15.9146 |
| 1.9301        | 32.0  | 1152 | 1.6661          | 1.4274 | 15.7317 |
| 1.9301        | 33.0  | 1188 | 1.6474          | 1.4484 | 15.6463 |
| 1.9301        | 34.0  | 1224 | 1.6484          | 1.5172 | 15.7805 |
| 1.9301        | 35.0  | 1260 | 1.6389          | 1.5497 | 15.7561 |
| 1.9301        | 36.0  | 1296 | 1.6384          | 1.52   | 15.6341 |
| 1.9301        | 37.0  | 1332 | 1.6304          | 1.4572 | 15.8293 |
| 1.9301        | 38.0  | 1368 | 1.6163          | 1.4786 | 16.1341 |
| 1.9301        | 39.0  | 1404 | 1.6116          | 1.5765 | 15.9634 |
| 1.9301        | 40.0  | 1440 | 1.6020          | 1.5902 | 16.0244 |
| 1.9301        | 41.0  | 1476 | 1.6064          | 1.6992 | 15.8659 |
| 1.6368        | 42.0  | 1512 | 1.5949          | 1.5409 | 16.0    |
| 1.6368        | 43.0  | 1548 | 1.5811          | 1.4916 | 16.2439 |
| 1.6368        | 44.0  | 1584 | 1.5849          | 1.6047 | 16.2683 |
| 1.6368        | 45.0  | 1620 | 1.5843          | 1.521  | 15.7073 |
| 1.6368        | 46.0  | 1656 | 1.5805          | 1.7424 | 15.9878 |
| 1.6368        | 47.0  | 1692 | 1.5791          | 1.6066 | 15.9268 |
| 1.6368        | 48.0  | 1728 | 1.5734          | 1.602  | 15.7195 |
| 1.6368        | 49.0  | 1764 | 1.5649          | 1.5817 | 15.939  |
| 1.6368        | 50.0  | 1800 | 1.5654          | 1.6469 | 15.8293 |
| 1.6368        | 51.0  | 1836 | 1.5587          | 1.7048 | 15.6463 |
| 1.6368        | 52.0  | 1872 | 1.5553          | 1.5203 | 15.8415 |
| 1.6368        | 53.0  | 1908 | 1.5500          | 1.5646 | 15.6951 |
| 1.6368        | 54.0  | 1944 | 1.5532          | 1.5003 | 15.7195 |
| 1.6368        | 55.0  | 1980 | 1.5344          | 1.5359 | 16.1098 |
| 1.4554        | 56.0  | 2016 | 1.5370          | 1.6052 | 15.6951 |
| 1.4554        | 57.0  | 2052 | 1.5394          | 1.5299 | 15.9146 |
| 1.4554        | 58.0  | 2088 | 1.5399          | 1.6024 | 15.6829 |
| 1.4554        | 59.0  | 2124 | 1.5403          | 1.6342 | 15.6829 |
| 1.4554        | 60.0  | 2160 | 1.5361          | 1.609  | 15.7195 |
| 1.4554        | 61.0  | 2196 | 1.5308          | 1.6753 | 15.878  |
| 1.4554        | 62.0  | 2232 | 1.5211          | 1.6381 | 16.0976 |
| 1.4554        | 63.0  | 2268 | 1.5242          | 1.7172 | 15.622  |
| 1.4554        | 64.0  | 2304 | 1.5215          | 1.6888 | 15.9024 |
| 1.4554        | 65.0  | 2340 | 1.5146          | 1.6619 | 16.0    |
| 1.4554        | 66.0  | 2376 | 1.5173          | 1.7203 | 15.8537 |
| 1.4554        | 67.0  | 2412 | 1.5235          | 1.7363 | 15.7317 |
| 1.4554        | 68.0  | 2448 | 1.5125          | 1.7295 | 16.0366 |
| 1.4554        | 69.0  | 2484 | 1.5141          | 1.7005 | 15.8902 |
| 1.3341        | 70.0  | 2520 | 1.5162          | 1.8302 | 15.7927 |
| 1.3341        | 71.0  | 2556 | 1.5129          | 1.8278 | 15.9024 |
| 1.3341        | 72.0  | 2592 | 1.5123          | 1.7764 | 15.6829 |
| 1.3341        | 73.0  | 2628 | 1.5046          | 1.7259 | 15.9634 |
| 1.3341        | 74.0  | 2664 | 1.5069          | 1.6517 | 15.9024 |
| 1.3341        | 75.0  | 2700 | 1.5026          | 1.7334 | 15.9024 |
| 1.3341        | 76.0  | 2736 | 1.4923          | 1.7531 | 15.9268 |
| 1.3341        | 77.0  | 2772 | 1.4956          | 1.7338 | 15.7561 |
| 1.3341        | 78.0  | 2808 | 1.4996          | 1.6956 | 15.7805 |
| 1.3341        | 79.0  | 2844 | 1.5010          | 1.7299 | 15.9268 |
| 1.3341        | 80.0  | 2880 | 1.5012          | 1.7097 | 15.9024 |
| 1.3341        | 81.0  | 2916 | 1.5032          | 1.7689 | 15.8902 |
| 1.3341        | 82.0  | 2952 | 1.5025          | 1.7353 | 15.939  |
| 1.3341        | 83.0  | 2988 | 1.5004          | 1.7472 | 15.9512 |
| 1.2568        | 84.0  | 3024 | 1.4989          | 1.7171 | 15.9756 |
| 1.2568        | 85.0  | 3060 | 1.5015          | 1.7704 | 15.9024 |
| 1.2568        | 86.0  | 3096 | 1.5017          | 1.7838 | 15.9024 |
| 1.2568        | 87.0  | 3132 | 1.5022          | 1.7562 | 16.0366 |
| 1.2568        | 88.0  | 3168 | 1.5004          | 1.7633 | 16.0366 |
| 1.2568        | 89.0  | 3204 | 1.4995          | 1.7633 | 15.9756 |
| 1.2568        | 90.0  | 3240 | 1.5038          | 1.766  | 15.8537 |
| 1.2568        | 91.0  | 3276 | 1.5001          | 1.7764 | 16.0    |
| 1.2568        | 92.0  | 3312 | 1.5010          | 1.7707 | 15.878  |
| 1.2568        | 93.0  | 3348 | 1.4996          | 1.7633 | 15.9268 |
| 1.2568        | 94.0  | 3384 | 1.5011          | 1.7453 | 15.8171 |
| 1.2568        | 95.0  | 3420 | 1.5014          | 1.7385 | 15.7927 |
| 1.2568        | 96.0  | 3456 | 1.4996          | 1.7253 | 15.7927 |
| 1.2568        | 97.0  | 3492 | 1.4988          | 1.7459 | 15.8049 |
| 1.2103        | 98.0  | 3528 | 1.4978          | 1.7461 | 15.8171 |
| 1.2103        | 99.0  | 3564 | 1.4986          | 1.7461 | 15.8293 |
| 1.2103        | 100.0 | 3600 | 1.4986          | 1.7461 | 15.8171 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "t5-base-finetuned-es-to-pua", "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-base-finetuned-es-to-pua
===========================


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


* Loss: 1.4986
* Bleu: 1.7461
* Gen Len: 15.8171


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.10.1
* Tokenizers 0.13.2