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# NLP-CIC-WFU_Clinical_Cases_NER_mBERT_cased_fine_tuned

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0501
- Precision: 0.8961
- Recall: 0.7009
- F1: 0.7865
- Accuracy: 0.9898

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 94   | 0.0484          | 0.9002    | 0.6340 | 0.7440 | 0.9876   |
| No log        | 2.0   | 188  | 0.0436          | 0.9095    | 0.6599 | 0.7649 | 0.9887   |
| No log        | 3.0   | 282  | 0.0462          | 0.8545    | 0.7043 | 0.7722 | 0.9883   |
| No log        | 4.0   | 376  | 0.0456          | 0.9058    | 0.6761 | 0.7743 | 0.9894   |
| No log        | 5.0   | 470  | 0.0447          | 0.9194    | 0.6836 | 0.7841 | 0.9900   |
| 0.0426        | 6.0   | 564  | 0.0480          | 0.8917    | 0.7026 | 0.7859 | 0.9897   |
| 0.0426        | 7.0   | 658  | 0.0501          | 0.8961    | 0.7009 | 0.7865 | 0.9898   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "NLP-CIC-WFU_Clinical_Cases_NER_mBERT_cased_fine_tuned", "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 

NLP-CIC-WFU\_Clinical\_Cases\_NER\_mBERT\_cased\_fine\_tuned
============================================================


This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0501
* Precision: 0.8961
* Recall: 0.7009
* F1: 0.7865
* Accuracy: 0.9898


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 #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: 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 #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: 7### Training results### Framework versions


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