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# consejo-ner

This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3066
- Precision: 0.7241
- Recall: 0.6774
- F1: 0.7
- Accuracy: 0.9313

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 15   | 1.5724          | 0.0       | 0.0    | 0.0    | 0.6985   |
| No log        | 2.0   | 30   | 1.3540          | 0.0       | 0.0    | 0.0    | 0.6985   |
| No log        | 3.0   | 45   | 1.0972          | 0.0       | 0.0    | 0.0    | 0.7099   |
| No log        | 4.0   | 60   | 0.8615          | 0.5833    | 0.2258 | 0.3256 | 0.7672   |
| No log        | 5.0   | 75   | 0.7381          | 0.5       | 0.3548 | 0.4151 | 0.8244   |
| No log        | 6.0   | 90   | 0.6111          | 0.5556    | 0.4839 | 0.5172 | 0.8473   |
| No log        | 7.0   | 105  | 0.5353          | 0.5185    | 0.4516 | 0.4828 | 0.8550   |
| No log        | 8.0   | 120  | 0.4786          | 0.5769    | 0.4839 | 0.5263 | 0.8626   |
| No log        | 9.0   | 135  | 0.4493          | 0.5357    | 0.4839 | 0.5085 | 0.8817   |
| No log        | 10.0  | 150  | 0.4269          | 0.4839    | 0.4839 | 0.4839 | 0.8779   |
| No log        | 11.0  | 165  | 0.3977          | 0.5938    | 0.6129 | 0.6032 | 0.8931   |
| No log        | 12.0  | 180  | 0.3669          | 0.5161    | 0.5161 | 0.5161 | 0.8969   |
| No log        | 13.0  | 195  | 0.3437          | 0.6786    | 0.6129 | 0.6441 | 0.9237   |
| No log        | 14.0  | 210  | 0.3389          | 0.6786    | 0.6129 | 0.6441 | 0.9198   |
| No log        | 15.0  | 225  | 0.3249          | 0.6786    | 0.6129 | 0.6441 | 0.9198   |
| No log        | 16.0  | 240  | 0.3102          | 0.6897    | 0.6452 | 0.6667 | 0.9275   |
| No log        | 17.0  | 255  | 0.3094          | 0.6667    | 0.6452 | 0.6557 | 0.9275   |
| No log        | 18.0  | 270  | 0.3159          | 0.7       | 0.6774 | 0.6885 | 0.9198   |
| No log        | 19.0  | 285  | 0.3094          | 0.7241    | 0.6774 | 0.7    | 0.9313   |
| No log        | 20.0  | 300  | 0.3066          | 0.7241    | 0.6774 | 0.7    | 0.9313   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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

consejo-ner
===========


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


* Loss: 0.3066
* Precision: 0.7241
* Recall: 0.6774
* F1: 0.7
* Accuracy: 0.9313


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: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #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: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #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: 20### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2