readme: ---
  
  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
  