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# modelBeto

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: 0.1719
- Precision: 0.5388
- Recall: 0.5781
- F1: 0.5578
- Accuracy: 0.9685

## 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   | 0.2382          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 2.0   | 58   | 0.2253          | 0.0       | 0.0    | 0.0    | 0.9473   |
| No log        | 3.0   | 87   | 0.1591          | 0.3922    | 0.1042 | 0.1646 | 0.9512   |
| No log        | 4.0   | 116  | 0.1398          | 0.3529    | 0.2188 | 0.2701 | 0.9590   |
| No log        | 5.0   | 145  | 0.1157          | 0.4468    | 0.3281 | 0.3784 | 0.9571   |
| No log        | 6.0   | 174  | 0.1181          | 0.5407    | 0.3802 | 0.4465 | 0.9604   |
| No log        | 7.0   | 203  | 0.1144          | 0.4384    | 0.5    | 0.4672 | 0.9597   |
| No log        | 8.0   | 232  | 0.1350          | 0.5887    | 0.4323 | 0.4985 | 0.9682   |
| No log        | 9.0   | 261  | 0.1193          | 0.5117    | 0.5677 | 0.5383 | 0.9649   |
| No log        | 10.0  | 290  | 0.1365          | 0.5962    | 0.4844 | 0.5345 | 0.9708   |
| No log        | 11.0  | 319  | 0.1352          | 0.5       | 0.5781 | 0.5362 | 0.9652   |
| No log        | 12.0  | 348  | 0.1534          | 0.5593    | 0.5156 | 0.5366 | 0.9692   |
| No log        | 13.0  | 377  | 0.1475          | 0.5838    | 0.5260 | 0.5534 | 0.9699   |
| No log        | 14.0  | 406  | 0.1395          | 0.5144    | 0.6510 | 0.5747 | 0.9670   |
| No log        | 15.0  | 435  | 0.1487          | 0.5550    | 0.6042 | 0.5786 | 0.9696   |
| No log        | 16.0  | 464  | 0.1576          | 0.5637    | 0.5990 | 0.5808 | 0.9697   |
| No log        | 17.0  | 493  | 0.1557          | 0.5699    | 0.5521 | 0.5608 | 0.9697   |
| 0.0779        | 18.0  | 522  | 0.1581          | 0.5062    | 0.6354 | 0.5635 | 0.9665   |
| 0.0779        | 19.0  | 551  | 0.1545          | 0.5312    | 0.6198 | 0.5721 | 0.9671   |
| 0.0779        | 20.0  | 580  | 0.1580          | 0.5870    | 0.5625 | 0.5745 | 0.9711   |
| 0.0779        | 21.0  | 609  | 0.1615          | 0.5498    | 0.6042 | 0.5757 | 0.9692   |
| 0.0779        | 22.0  | 638  | 0.1607          | 0.5289    | 0.6198 | 0.5707 | 0.9678   |
| 0.0779        | 23.0  | 667  | 0.1648          | 0.5619    | 0.5677 | 0.5648 | 0.9687   |
| 0.0779        | 24.0  | 696  | 0.1686          | 0.5459    | 0.5885 | 0.5664 | 0.9677   |
| 0.0779        | 25.0  | 725  | 0.1659          | 0.5463    | 0.5833 | 0.5642 | 0.9680   |
| 0.0779        | 26.0  | 754  | 0.1668          | 0.5567    | 0.5885 | 0.5722 | 0.9694   |
| 0.0779        | 27.0  | 783  | 0.1681          | 0.5392    | 0.6094 | 0.5721 | 0.9684   |
| 0.0779        | 28.0  | 812  | 0.1693          | 0.5534    | 0.5938 | 0.5729 | 0.9690   |
| 0.0779        | 29.0  | 841  | 0.1723          | 0.5441    | 0.5781 | 0.5606 | 0.9684   |
| 0.0779        | 30.0  | 870  | 0.1710          | 0.5308    | 0.5833 | 0.5558 | 0.9680   |
| 0.0779        | 31.0  | 899  | 0.1718          | 0.5388    | 0.5781 | 0.5578 | 0.9684   |
| 0.0779        | 32.0  | 928  | 0.1719          | 0.5388    | 0.5781 | 0.5578 | 0.9685   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "modelBeto", "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 

modelBeto
=========


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: 0.1719
* Precision: 0.5388
* Recall: 0.5781
* F1: 0.5578
* Accuracy: 0.9685


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 2.11.0
* 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 2.11.0
* 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 2.11.0
* 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 2.11.0
* Tokenizers 0.13.3