---

license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-cased-cv-studio_name-medium
  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"
- text: "mi nombre es Ivan Ducales Marquez, hago de subpresidente en la republica de Colombia. tengo experiencia en seguir órdenes de mis patrocinadores y repartir los recursos del país a empresarios corruptos"
---

<!-- 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-cv-studio_name-medium

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: 2.3310
- F1 Micro: 0.6388
- F1 Macro: 0.5001

## Model description

Predicts a studio name based on a CV text


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Micro | F1 Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:------------:|
| 1.4139        | 0.98  | 1000  | 1.3831          | 0.6039   | 0.6039   | 0.4188   | 0.6039          | 0.6039       |
| 1.1561        | 1.96  | 2000  | 1.2386          | 0.6554   | 0.6554   | 0.4743   | 0.6554          | 0.6554       |
| 0.9183        | 2.93  | 3000  | 1.2201          | 0.6576   | 0.6576   | 0.5011   | 0.6576          | 0.6576       |
| 0.677         | 3.91  | 4000  | 1.3478          | 0.6442   | 0.6442   | 0.5206   | 0.6442          | 0.6442       |
| 0.4857        | 4.89  | 5000  | 1.4765          | 0.6393   | 0.6393   | 0.5215   | 0.6393          | 0.6393       |
| 0.3318        | 5.87  | 6000  | 1.6924          | 0.6442   | 0.6442   | 0.5024   | 0.6442          | 0.6442       |
| 0.2273        | 6.84  | 7000  | 1.8645          | 0.6444   | 0.6444   | 0.5060   | 0.6444          | 0.6444       |
| 0.1396        | 7.82  | 8000  | 2.1143          | 0.6381   | 0.6381   | 0.5181   | 0.6381          | 0.6381       |
| 0.0841        | 8.8   | 9000  | 2.2699          | 0.6359   | 0.6359   | 0.5065   | 0.6359          | 0.6359       |
| 0.0598        | 9.78  | 10000 | 2.3310          | 0.6388   | 0.6388   | 0.5001   | 0.6388          | 0.6388       |


### Framework versions

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