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# 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "widget": [{"text": "Egresado de la carrera Ingenier\u00eda en Computaci\u00f3n Conocimientos de lenguajes HTML, CSS, Javascript y MySQL. Experiencia trabajando en \u00e1mbitos de redes de peque\u00f1a y mediana escala. Ingl\u00e9s Hablado nivel b\u00e1sico, 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 \u00f3rdenes de mis patrocinadores y repartir los recursos del pa\u00eds a empresarios corruptos"}], "model-index": [{"name": "bert-base-cased-cv-studio_name-medium", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-base-cased-cv-studio\_name-medium
======================================


This model is a fine-tuned version of 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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.19.0
* Pytorch 1.8.2+cu111
* Datasets 1.6.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.19.0
* Pytorch 1.8.2+cu111
* Datasets 1.6.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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