---
library_name: transformers
base_model: dccuchile/albert-base-spanish-finetuned-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: albert-base-spanish-finetuned-ner-finetuned-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. -->

# albert-base-spanish-finetuned-ner-finetuned-ner

This model is a fine-tuned version of [dccuchile/albert-base-spanish-finetuned-ner](https://huggingface.co/dccuchile/albert-base-spanish-finetuned-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3012
- Precision: 0.8356
- Recall: 0.8356
- F1: 0.8356
- Accuracy: 0.9385

## 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   | 13   | 1.8849          | 0.0       | 0.0    | 0.0    | 0.5939   |
| No log        | 2.0   | 26   | 1.4600          | 0.0       | 0.0    | 0.0    | 0.6687   |
| No log        | 3.0   | 39   | 1.1449          | 0.0       | 0.0    | 0.0    | 0.6832   |
| No log        | 4.0   | 52   | 0.9138          | 0.2857    | 0.2329 | 0.2566 | 0.8056   |
| No log        | 5.0   | 65   | 0.7441          | 0.4504    | 0.4041 | 0.4260 | 0.8399   |
| No log        | 6.0   | 78   | 0.6292          | 0.5310    | 0.5274 | 0.5292 | 0.875    |
| No log        | 7.0   | 91   | 0.5406          | 0.6786    | 0.6507 | 0.6643 | 0.9041   |
| No log        | 8.0   | 104  | 0.4747          | 0.7397    | 0.7397 | 0.7397 | 0.9259   |
| No log        | 9.0   | 117  | 0.4228          | 0.7945    | 0.7945 | 0.7945 | 0.9306   |
| No log        | 10.0  | 130  | 0.3900          | 0.8333    | 0.8219 | 0.8276 | 0.9332   |
| No log        | 11.0  | 143  | 0.3685          | 0.8392    | 0.8219 | 0.8304 | 0.9339   |
| No log        | 12.0  | 156  | 0.3487          | 0.8333    | 0.8219 | 0.8276 | 0.9339   |
| No log        | 13.0  | 169  | 0.3325          | 0.8219    | 0.8219 | 0.8219 | 0.9339   |
| No log        | 14.0  | 182  | 0.3227          | 0.8472    | 0.8356 | 0.8414 | 0.9339   |
| No log        | 15.0  | 195  | 0.3150          | 0.8531    | 0.8356 | 0.8443 | 0.9358   |
| No log        | 16.0  | 208  | 0.3094          | 0.8345    | 0.8288 | 0.8316 | 0.9358   |
| No log        | 17.0  | 221  | 0.3047          | 0.8414    | 0.8356 | 0.8385 | 0.9378   |
| No log        | 18.0  | 234  | 0.3027          | 0.8356    | 0.8356 | 0.8356 | 0.9385   |
| No log        | 19.0  | 247  | 0.3017          | 0.8414    | 0.8356 | 0.8385 | 0.9385   |
| No log        | 20.0  | 260  | 0.3012          | 0.8356    | 0.8356 | 0.8356 | 0.9385   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1