---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: spa-eng-pos-tagging-v2.1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# spa-eng-pos-tagging-v2.1

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1523
- Accuracy: 0.9516
- Precision: 0.9445
- Recall: 0.8846
- F1: 0.8831
- Hamming Loss: 0.0484

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming Loss |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
| 0.3806        | 1.0   | 1744  | 0.2730          | 0.8940   | 0.8903    | 0.8246 | 0.8252 | 0.1060       |
| 0.2615        | 2.0   | 3488  | 0.2134          | 0.9181   | 0.9058    | 0.8514 | 0.8464 | 0.0819       |
| 0.1864        | 3.0   | 5232  | 0.1895          | 0.9284   | 0.9224    | 0.8626 | 0.8608 | 0.0716       |
| 0.1721        | 4.0   | 6976  | 0.1769          | 0.9352   | 0.9287    | 0.8676 | 0.8667 | 0.0648       |
| 0.1462        | 5.0   | 8720  | 0.1840          | 0.9355   | 0.9310    | 0.8663 | 0.8670 | 0.0645       |
| 0.1175        | 6.0   | 10464 | 0.1553          | 0.9487   | 0.9399    | 0.8820 | 0.8794 | 0.0513       |
| 0.0949        | 7.0   | 12208 | 0.1523          | 0.9516   | 0.9445    | 0.8846 | 0.8831 | 0.0484       |
| 0.0833        | 8.0   | 13952 | 0.1564          | 0.9535   | 0.9439    | 0.8881 | 0.8847 | 0.0465       |
| 0.0722        | 9.0   | 15696 | 0.1566          | 0.9549   | 0.9472    | 0.8890 | 0.8867 | 0.0451       |
| 0.0571        | 10.0  | 17440 | 0.1649          | 0.9565   | 0.9513    | 0.8875 | 0.8880 | 0.0435       |
| 0.0516        | 11.0  | 19184 | 0.1669          | 0.9587   | 0.9523    | 0.8913 | 0.8905 | 0.0413       |
| 0.0392        | 12.0  | 20928 | 0.1711          | 0.9598   | 0.9524    | 0.8925 | 0.8911 | 0.0402       |
| 0.03          | 13.0  | 22672 | 0.1800          | 0.9603   | 0.9533    | 0.8935 | 0.8921 | 0.0397       |
| 0.0308        | 14.0  | 24416 | 0.1827          | 0.9607   | 0.9537    | 0.8938 | 0.8924 | 0.0393       |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3