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# 5

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: 0.2255
- Precision: 0.6432
- Recall: 0.595
- F1: 0.6182
- Accuracy: 0.9709

## 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: 5.5e-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   | 0.3210          | 0.0       | 0.0    | 0.0    | 0.9324   |
| No log        | 2.0   | 58   | 0.2694          | 0.0       | 0.0    | 0.0    | 0.9324   |
| No log        | 3.0   | 87   | 0.2216          | 0.0       | 0.0    | 0.0    | 0.9316   |
| No log        | 4.0   | 116  | 0.2115          | 0.25      | 0.035  | 0.0614 | 0.9403   |
| No log        | 5.0   | 145  | 0.1740          | 0.3465    | 0.175  | 0.2326 | 0.9512   |
| No log        | 6.0   | 174  | 0.1589          | 0.42      | 0.315  | 0.36   | 0.9566   |
| No log        | 7.0   | 203  | 0.1514          | 0.4797    | 0.295  | 0.3653 | 0.9584   |
| No log        | 8.0   | 232  | 0.1686          | 0.4576    | 0.405  | 0.4297 | 0.9624   |
| No log        | 9.0   | 261  | 0.1840          | 0.5971    | 0.415  | 0.4897 | 0.9646   |
| No log        | 10.0  | 290  | 0.1571          | 0.5505    | 0.545  | 0.5477 | 0.9646   |
| No log        | 11.0  | 319  | 0.1809          | 0.6158    | 0.545  | 0.5782 | 0.9700   |
| No log        | 12.0  | 348  | 0.1763          | 0.6129    | 0.57   | 0.5907 | 0.9681   |
| No log        | 13.0  | 377  | 0.1902          | 0.5571    | 0.61   | 0.5823 | 0.9655   |
| No log        | 14.0  | 406  | 0.1916          | 0.5842    | 0.555  | 0.5692 | 0.9673   |
| No log        | 15.0  | 435  | 0.1895          | 0.6335    | 0.605  | 0.6189 | 0.9697   |
| No log        | 16.0  | 464  | 0.1951          | 0.5880    | 0.635  | 0.6106 | 0.9667   |
| No log        | 17.0  | 493  | 0.1918          | 0.6324    | 0.585  | 0.6078 | 0.9702   |
| 0.0838        | 18.0  | 522  | 0.1957          | 0.6020    | 0.605  | 0.6035 | 0.9699   |
| 0.0838        | 19.0  | 551  | 0.1886          | 0.6       | 0.6    | 0.6    | 0.9681   |
| 0.0838        | 20.0  | 580  | 0.1992          | 0.6158    | 0.585  | 0.6    | 0.9702   |
| 0.0838        | 21.0  | 609  | 0.2043          | 0.625     | 0.6    | 0.6122 | 0.9706   |
| 0.0838        | 22.0  | 638  | 0.2110          | 0.6243    | 0.59   | 0.6067 | 0.9707   |
| 0.0838        | 23.0  | 667  | 0.2121          | 0.6421    | 0.61   | 0.6256 | 0.9714   |
| 0.0838        | 24.0  | 696  | 0.2112          | 0.6455    | 0.61   | 0.6272 | 0.9713   |
| 0.0838        | 25.0  | 725  | 0.2150          | 0.6392    | 0.62   | 0.6294 | 0.9711   |
| 0.0838        | 26.0  | 754  | 0.2229          | 0.6264    | 0.57   | 0.5969 | 0.9702   |
| 0.0838        | 27.0  | 783  | 0.2219          | 0.6339    | 0.58   | 0.6057 | 0.9706   |
| 0.0838        | 28.0  | 812  | 0.2239          | 0.6429    | 0.585  | 0.6126 | 0.9707   |
| 0.0838        | 29.0  | 841  | 0.2211          | 0.6402    | 0.605  | 0.6221 | 0.9713   |
| 0.0838        | 30.0  | 870  | 0.2230          | 0.6364    | 0.595  | 0.6150 | 0.9709   |
| 0.0838        | 31.0  | 899  | 0.2244          | 0.6432    | 0.595  | 0.6182 | 0.9709   |
| 0.0838        | 32.0  | 928  | 0.2255          | 0.6432    | 0.595  | 0.6182 | 0.9709   |


### 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": "5", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

5
=


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: 0.2255
* Precision: 0.6432
* Recall: 0.595
* F1: 0.6182
* Accuracy: 0.9709


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: 5.5e-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: 5.5e-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 #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.5e-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