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# modelBeto5

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1686
- Precision: 0.5990
- Recall: 0.6541
- F1: 0.6253
- Accuracy: 0.9727

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2706          | 0.0       | 0.0    | 0.0    | 0.9451   |
| No log        | 2.0   | 58   | 0.3328          | 0.0       | 0.0    | 0.0    | 0.9451   |
| No log        | 3.0   | 87   | 0.1872          | 0.0476    | 0.0108 | 0.0176 | 0.9320   |
| No log        | 4.0   | 116  | 0.1428          | 0.3971    | 0.1459 | 0.2134 | 0.9551   |
| No log        | 5.0   | 145  | 0.1169          | 0.4690    | 0.2865 | 0.3557 | 0.9614   |
| No log        | 6.0   | 174  | 0.1259          | 0.5414    | 0.5297 | 0.5355 | 0.9629   |
| No log        | 7.0   | 203  | 0.1166          | 0.4575    | 0.6108 | 0.5231 | 0.9604   |
| No log        | 8.0   | 232  | 0.1240          | 0.6149    | 0.4919 | 0.5465 | 0.9693   |
| No log        | 9.0   | 261  | 0.1145          | 0.5276    | 0.5676 | 0.5469 | 0.9681   |
| No log        | 10.0  | 290  | 0.1377          | 0.5612    | 0.5946 | 0.5774 | 0.9688   |
| No log        | 11.0  | 319  | 0.1321          | 0.5833    | 0.6432 | 0.6118 | 0.9700   |
| No log        | 12.0  | 348  | 0.1549          | 0.6581    | 0.5514 | 0.6    | 0.9717   |
| No log        | 13.0  | 377  | 0.1482          | 0.6080    | 0.6541 | 0.6302 | 0.9713   |
| No log        | 14.0  | 406  | 0.1589          | 0.5348    | 0.6649 | 0.5928 | 0.9675   |
| No log        | 15.0  | 435  | 0.1507          | 0.6178    | 0.6378 | 0.6277 | 0.9720   |
| No log        | 16.0  | 464  | 0.1554          | 0.6082    | 0.6378 | 0.6227 | 0.9720   |
| No log        | 17.0  | 493  | 0.1658          | 0.5918    | 0.6270 | 0.6089 | 0.9708   |
| 0.0785        | 18.0  | 522  | 0.1616          | 0.5792    | 0.6919 | 0.6305 | 0.9715   |
| 0.0785        | 19.0  | 551  | 0.1632          | 0.6059    | 0.6649 | 0.6340 | 0.9717   |
| 0.0785        | 20.0  | 580  | 0.1638          | 0.6103    | 0.6432 | 0.6263 | 0.9726   |
| 0.0785        | 21.0  | 609  | 0.1603          | 0.6010    | 0.6432 | 0.6214 | 0.9724   |
| 0.0785        | 22.0  | 638  | 0.1652          | 0.6078    | 0.6703 | 0.6375 | 0.9722   |
| 0.0785        | 23.0  | 667  | 0.1577          | 0.6440    | 0.6649 | 0.6543 | 0.9738   |
| 0.0785        | 24.0  | 696  | 0.1600          | 0.6492    | 0.6703 | 0.6596 | 0.9743   |
| 0.0785        | 25.0  | 725  | 0.1663          | 0.6256    | 0.6595 | 0.6421 | 0.9733   |
| 0.0785        | 26.0  | 754  | 0.1686          | 0.6106    | 0.6865 | 0.6463 | 0.9713   |
| 0.0785        | 27.0  | 783  | 0.1691          | 0.5951    | 0.6595 | 0.6256 | 0.9720   |
| 0.0785        | 28.0  | 812  | 0.1668          | 0.61      | 0.6595 | 0.6338 | 0.9731   |
| 0.0785        | 29.0  | 841  | 0.1679          | 0.5931    | 0.6541 | 0.6221 | 0.9724   |
| 0.0785        | 30.0  | 870  | 0.1678          | 0.6162    | 0.6595 | 0.6371 | 0.9734   |
| 0.0785        | 31.0  | 899  | 0.1683          | 0.6040    | 0.6595 | 0.6305 | 0.9729   |
| 0.0785        | 32.0  | 928  | 0.1686          | 0.5990    | 0.6541 | 0.6253 | 0.9727   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "modelBeto5", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

modelBeto5
==========


This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1686
* Precision: 0.5990
* Recall: 0.6541
* F1: 0.6253
* Accuracy: 0.9727


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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3