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# roberta-finetuned-CPV_Spanish

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0422
- F1: 0.7739
- Roc Auc: 0.8704
- Accuracy: 0.7201
- Coverage Error: 11.5798
- Label Ranking Average Precision Score: 0.7742

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy | Coverage Error | Label Ranking Average Precision Score |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0579        | 1.0   | 2039  | 0.0548          | 0.6327 | 0.7485  | 0.5274   | 21.7879        | 0.5591                                |
| 0.0411        | 2.0   | 4078  | 0.0441          | 0.7108 | 0.8027  | 0.6386   | 16.8647        | 0.6732                                |
| 0.0294        | 3.0   | 6117  | 0.0398          | 0.7437 | 0.8295  | 0.6857   | 14.6700        | 0.7249                                |
| 0.0223        | 4.0   | 8156  | 0.0389          | 0.7568 | 0.8453  | 0.7056   | 13.3552        | 0.7494                                |
| 0.0163        | 5.0   | 10195 | 0.0397          | 0.7626 | 0.8569  | 0.7097   | 12.5895        | 0.7620                                |
| 0.0132        | 6.0   | 12234 | 0.0395          | 0.7686 | 0.8620  | 0.7126   | 12.1926        | 0.7656                                |
| 0.0095        | 7.0   | 14273 | 0.0409          | 0.7669 | 0.8694  | 0.7109   | 11.5978        | 0.7700                                |
| 0.0066        | 8.0   | 16312 | 0.0415          | 0.7705 | 0.8726  | 0.7107   | 11.4252        | 0.7714                                |
| 0.0055        | 9.0   | 18351 | 0.0417          | 0.7720 | 0.8689  | 0.7163   | 11.6987        | 0.7716                                |
| 0.0045        | 10.0  | 20390 | 0.0422          | 0.7739 | 0.8704  | 0.7201   | 11.5798        | 0.7742                                |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "roberta-finetuned-CPV_Spanish", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

roberta-finetuned-CPV\_Spanish
==============================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0422
* F1: 0.7739
* Roc Auc: 0.8704
* Accuracy: 0.7201
* Coverage Error: 11.5798
* Label Ranking Average Precision Score: 0.7742


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: 2e-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: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #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: 2e-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: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #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: 2e-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: 10### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1