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---
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
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