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# NLP-CIC-WFU_Clinical_Cases_NER_Sents_Tokenized_bertin_roberta_base_spanish_fine_tuned

This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- Precision: 0.9012
- Recall: 0.6942
- F1: 0.7842
- Accuracy: 0.9857

## 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: 5e-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: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0605        | 1.0   | 2568  | 0.0625          | 0.9400    | 0.6322 | 0.7560 | 0.9836   |
| 0.0475        | 2.0   | 5136  | 0.0622          | 0.9533    | 0.6572 | 0.7781 | 0.9849   |
| 0.0374        | 3.0   | 7704  | 0.0552          | 0.9261    | 0.6784 | 0.7831 | 0.9855   |
| 0.0246        | 4.0   | 10272 | 0.0693          | 0.9381    | 0.6658 | 0.7788 | 0.9849   |
| 0.0126        | 5.0   | 12840 | 0.0974          | 0.8918    | 0.6830 | 0.7735 | 0.9849   |
| 0.0061        | 6.0   | 15408 | 0.0886          | 0.8771    | 0.7099 | 0.7847 | 0.9850   |
| 0.0031        | 7.0   | 17976 | 0.0973          | 0.9012    | 0.6942 | 0.7842 | 0.9857   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "NLP-CIC-WFU_Clinical_Cases_NER_Sents_Tokenized_bertin_roberta_base_spanish_fine_tuned", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 

NLP-CIC-WFU\_Clinical\_Cases\_NER\_Sents\_Tokenized\_bertin\_roberta\_base\_spanish\_fine\_tuned
================================================================================================


This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0973
* Precision: 0.9012
* Recall: 0.6942
* F1: 0.7842
* Accuracy: 0.9857


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: 5e-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: 7


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 7 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 7 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 7### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1