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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-cased-fine-tuning-cvs-hf-studio-name
  results: []
  
widget:
- text: "Egresado de la carrera Ingeniería en Computación Conocimientos de lenguajes HTML, CSS, Javascript y MySQL. Experiencia trabajando en ámbitos de redes de pequeña y mediana escala. Inglés Hablado nivel básico, escrito nivel intermedio.HTML, CSS y JavaScript. Realidad aumentada.  Lenguaje R. HTML5, JavaScript y Nodejs"

---

<!-- 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. -->

# bert-base-cased-fine-tuning-cvs-hf-studio-name

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2601
- Accuracy: 0.6500
- F1: 0.6500
- Precision: 0.6500
- Recall: 0.6500

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.4407        | 0.24  | 500  | 1.5664          | 0.5528   | 0.5528 | 0.5528    | 0.5528 |
| 1.3055        | 0.49  | 1000 | 1.4891          | 0.5745   | 0.5745 | 0.5745    | 0.5745 |
| 1.373         | 0.73  | 1500 | 1.3634          | 0.6180   | 0.6180 | 0.6180    | 0.6180 |
| 1.3621        | 0.98  | 2000 | 1.3768          | 0.6139   | 0.6139 | 0.6139    | 0.6139 |
| 1.1677        | 1.22  | 2500 | 1.3330          | 0.6395   | 0.6395 | 0.6395    | 0.6395 |
| 1.0826        | 1.47  | 3000 | 1.4003          | 0.6146   | 0.6146 | 0.6146    | 0.6146 |
| 1.0968        | 1.71  | 3500 | 1.2601          | 0.6500   | 0.6500 | 0.6500    | 0.6500 |
| 1.0896        | 1.96  | 4000 | 1.2826          | 0.6564   | 0.6564 | 0.6564    | 0.6564 |
| 0.8572        | 2.2   | 4500 | 1.3254          | 0.6569   | 0.6569 | 0.6569    | 0.6569 |
| 0.822         | 2.44  | 5000 | 1.3024          | 0.6571   | 0.6571 | 0.6571    | 0.6571 |
| 0.8022        | 2.69  | 5500 | 1.2971          | 0.6608   | 0.6608 | 0.6608    | 0.6608 |
| 0.834         | 2.93  | 6000 | 1.2900          | 0.6630   | 0.6630 | 0.6630    | 0.6630 |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.8.2+cu111
- Datasets 1.6.2
- Tokenizers 0.12.1
