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# Species_Identification_mBERT_fine_tuned_Train_Test

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the [LivingNER dataset] (https://temu.bsc.es/livingner/). This is a result of the PhD dissertation of Antonio Tamayo.
It achieves the following results on the evaluation set:
- Loss: 0.0364
- Precision: 0.9493
- Recall: 0.9484
- F1: 0.9489
- Accuracy: 0.9957

## 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: 2e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0038        | 1.0   | 3477  | 0.0280          | 0.9531    | 0.9279 | 0.9403 | 0.9950   |
| 0.0035        | 2.0   | 6954  | 0.0314          | 0.9415    | 0.9405 | 0.9410 | 0.9951   |
| 0.0018        | 3.0   | 10431 | 0.0346          | 0.9542    | 0.9264 | 0.9401 | 0.9951   |
| 0.0017        | 4.0   | 13908 | 0.0306          | 0.9451    | 0.9378 | 0.9414 | 0.9951   |
| 0.0004        | 5.0   | 17385 | 0.0346          | 0.9413    | 0.9509 | 0.9461 | 0.9955   |
| 0.0002        | 6.0   | 20862 | 0.0368          | 0.9507    | 0.9426 | 0.9466 | 0.9955   |
| 0.0006        | 7.0   | 24339 | 0.0364          | 0.9493    | 0.9484 | 0.9489 | 0.9957   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "widget": [{"text": "La paciente present\u00f3 anemizaci\u00f3n que ha ido recuperando sin que haya precisado hemotransfusi\u00f3n."}], "model-index": [{"name": "Species_Identification_mBERT_fine_tuned_Train_Test", "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 

Species\_Identification\_mBERT\_fine\_tuned\_Train\_Test
========================================================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-biomedical-clinical-es on the [LivingNER dataset] (URL This is a result of the PhD dissertation of Antonio Tamayo.
It achieves the following results on the evaluation set:


* Loss: 0.0364
* Precision: 0.9493
* Recall: 0.9484
* F1: 0.9489
* Accuracy: 0.9957


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: 2e-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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* 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: 2e-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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3