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# BERT_ep6_lr3

This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1098
- Precision: 0.7406
- Recall: 0.8132
- F1: 0.7752
- Accuracy: 0.9638

## 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-07
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.1408          | 0.6915    | 0.7505 | 0.7198 | 0.9556   |
| 0.1799        | 2.0   | 934  | 0.1215          | 0.7135    | 0.7790 | 0.7448 | 0.9602   |
| 0.1233        | 3.0   | 1401 | 0.1151          | 0.7248    | 0.8002 | 0.7606 | 0.9618   |
| 0.1131        | 4.0   | 1868 | 0.1120          | 0.7362    | 0.8099 | 0.7713 | 0.9631   |
| 0.1038        | 5.0   | 2335 | 0.1103          | 0.7399    | 0.8118 | 0.7742 | 0.9637   |
| 0.1025        | 6.0   | 2802 | 0.1098          | 0.7406    | 0.8132 | 0.7752 | 0.9638   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "BERT_ep6_lr3", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

BERT\_ep6\_lr3
==============


This model is a fine-tuned version of ajtamayoh/NER\_EHR\_Spanish\_model\_Mulitlingual\_BERT on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1098
* Precision: 0.7406
* Recall: 0.8132
* F1: 0.7752
* Accuracy: 0.9638


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-07
* 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: 6


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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: 6 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-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-07
* 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: 6 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-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-07
* 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: 6### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2