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# BERT_ep8_lr1

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: 0.1511
- Precision: 0.8632
- Recall: 0.8810
- F1: 0.8720
- Accuracy: 0.9767

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.0949          | 0.8056    | 0.8604 | 0.8321 | 0.9704   |
| 0.101         | 2.0   | 934  | 0.0978          | 0.8174    | 0.8876 | 0.8511 | 0.9725   |
| 0.0544        | 3.0   | 1401 | 0.0959          | 0.8384    | 0.8785 | 0.8580 | 0.9739   |
| 0.0331        | 4.0   | 1868 | 0.1018          | 0.8497    | 0.8841 | 0.8665 | 0.9749   |
| 0.0182        | 5.0   | 2335 | 0.1375          | 0.8658    | 0.8686 | 0.8672 | 0.9758   |
| 0.0133        | 6.0   | 2802 | 0.1458          | 0.8547    | 0.8843 | 0.8692 | 0.9753   |
| 0.0064        | 7.0   | 3269 | 0.1418          | 0.8628    | 0.8813 | 0.8719 | 0.9763   |
| 0.0041        | 8.0   | 3736 | 0.1511          | 0.8632    | 0.8810 | 0.8720 | 0.9767   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "BERT_ep8_lr1", "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\_ep8\_lr1
==============


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: 0.1511
* Precision: 0.8632
* Recall: 0.8810
* F1: 0.8720
* Accuracy: 0.9767


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: 8


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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: 8 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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-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: 8 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3