---
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-v1.3
  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-v1.3

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: 0.1650
- Accuracy: 0.9471
- Precision: 0.9372
- Recall: 0.8815
- F1: 0.8779
- Hamming Loss: 0.0529

## 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: 5e-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: 16

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming Loss |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
| 0.3809        | 1.0   | 1744  | 0.2945          | 0.8919   | 0.8798    | 0.8290 | 0.8221 | 0.1081       |
| 0.2625        | 2.0   | 3488  | 0.2725          | 0.8975   | 0.9004    | 0.8279 | 0.8319 | 0.1025       |
| 0.1918        | 3.0   | 5232  | 0.1901          | 0.9317   | 0.9224    | 0.8645 | 0.8618 | 0.0683       |
| 0.1674        | 4.0   | 6976  | 0.1780          | 0.9369   | 0.9319    | 0.8695 | 0.8694 | 0.0631       |
| 0.1478        | 5.0   | 8720  | 0.1816          | 0.9385   | 0.9303    | 0.8735 | 0.8697 | 0.0615       |
| 0.1201        | 6.0   | 10464 | 0.1650          | 0.9471   | 0.9372    | 0.8815 | 0.8779 | 0.0529       |
| 0.096         | 7.0   | 12208 | 0.1663          | 0.9493   | 0.9390    | 0.8851 | 0.8806 | 0.0507       |
| 0.0844        | 8.0   | 13952 | 0.1715          | 0.9500   | 0.9421    | 0.8838 | 0.8815 | 0.0500       |
| 0.0687        | 9.0   | 15696 | 0.1877          | 0.9502   | 0.9433    | 0.8816 | 0.8811 | 0.0498       |
| 0.0573        | 10.0  | 17440 | 0.1949          | 0.9483   | 0.9444    | 0.8781 | 0.8799 | 0.0517       |
| 0.0533        | 11.0  | 19184 | 0.1960          | 0.9544   | 0.9450    | 0.8872 | 0.8847 | 0.0456       |
| 0.0399        | 12.0  | 20928 | 0.2012          | 0.9565   | 0.9494    | 0.8884 | 0.8876 | 0.0435       |
| 0.031         | 13.0  | 22672 | 0.2119          | 0.9571   | 0.9496    | 0.8889 | 0.8879 | 0.0429       |
| 0.0292        | 14.0  | 24416 | 0.2213          | 0.9587   | 0.9512    | 0.8906 | 0.8896 | 0.0413       |
| 0.024         | 15.0  | 26160 | 0.2274          | 0.9587   | 0.9517    | 0.8899 | 0.8895 | 0.0413       |
| 0.0198        | 16.0  | 27904 | 0.2314          | 0.9591   | 0.8894    | 0.8905 | 0.8899 | 0.0409       |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3