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---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: consejo-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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
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