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# BERT_ep8_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: 0.1048
- Precision: 0.7641
- Recall: 0.8235
- F1: 0.7927
- Accuracy: 0.9666

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.1361          | 0.6936    | 0.7475 | 0.7195 | 0.9568   |
| 0.1814        | 2.0   | 934  | 0.1187          | 0.7168    | 0.7849 | 0.7493 | 0.9613   |
| 0.1202        | 3.0   | 1401 | 0.1118          | 0.7361    | 0.7990 | 0.7662 | 0.9635   |
| 0.1109        | 4.0   | 1868 | 0.1088          | 0.7508    | 0.8072 | 0.7780 | 0.9650   |
| 0.1006        | 5.0   | 2335 | 0.1069          | 0.7570    | 0.8158 | 0.7853 | 0.9657   |
| 0.0987        | 6.0   | 2802 | 0.1056          | 0.7604    | 0.8191 | 0.7887 | 0.9662   |
| 0.0969        | 7.0   | 3269 | 0.1050          | 0.7651    | 0.8224 | 0.7927 | 0.9665   |
| 0.0993        | 8.0   | 3736 | 0.1048          | 0.7641    | 0.8235 | 0.7927 | 0.9666   |


### 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_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\_ep8\_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: 0.1048
* Precision: 0.7641
* Recall: 0.8235
* F1: 0.7927
* Accuracy: 0.9666


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


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