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# modelBsc

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1830
- Precision: 0.64
- Recall: 0.6207
- F1: 0.6302
- Accuracy: 0.9685

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.3033          | 0.0213    | 0.0043 | 0.0072 | 0.9174   |
| No log        | 2.0   | 58   | 0.2425          | 0.1522    | 0.0302 | 0.0504 | 0.9325   |
| No log        | 3.0   | 87   | 0.1906          | 0.3056    | 0.1422 | 0.1941 | 0.9435   |
| No log        | 4.0   | 116  | 0.1825          | 0.3841    | 0.2716 | 0.3182 | 0.9439   |
| No log        | 5.0   | 145  | 0.1594          | 0.5517    | 0.3448 | 0.4244 | 0.9554   |
| No log        | 6.0   | 174  | 0.1383          | 0.5408    | 0.5431 | 0.5419 | 0.9595   |
| No log        | 7.0   | 203  | 0.1460          | 0.5897    | 0.4957 | 0.5386 | 0.9624   |
| No log        | 8.0   | 232  | 0.1534          | 0.6105    | 0.5    | 0.5498 | 0.9642   |
| No log        | 9.0   | 261  | 0.1587          | 0.5869    | 0.5388 | 0.5618 | 0.9631   |
| No log        | 10.0  | 290  | 0.1684          | 0.5921    | 0.5819 | 0.5870 | 0.9637   |
| No log        | 11.0  | 319  | 0.1713          | 0.5270    | 0.6724 | 0.5909 | 0.9606   |
| No log        | 12.0  | 348  | 0.1895          | 0.4984    | 0.6897 | 0.5787 | 0.9572   |
| No log        | 13.0  | 377  | 0.1759          | 0.4969    | 0.6897 | 0.5776 | 0.9568   |
| No log        | 14.0  | 406  | 0.1798          | 0.6468    | 0.5603 | 0.6005 | 0.9664   |
| No log        | 15.0  | 435  | 0.1909          | 0.5118    | 0.6552 | 0.5747 | 0.9597   |
| No log        | 16.0  | 464  | 0.1745          | 0.6184    | 0.6078 | 0.6130 | 0.9658   |
| No log        | 17.0  | 493  | 0.1670          | 0.6261    | 0.6207 | 0.6234 | 0.9674   |
| 0.062         | 18.0  | 522  | 0.1719          | 0.5992    | 0.6509 | 0.6240 | 0.9667   |
| 0.062         | 19.0  | 551  | 0.1759          | 0.6224    | 0.6466 | 0.6342 | 0.9674   |
| 0.062         | 20.0  | 580  | 0.1780          | 0.6327    | 0.6164 | 0.6245 | 0.9669   |
| 0.062         | 21.0  | 609  | 0.1777          | 0.5632    | 0.6336 | 0.5963 | 0.9637   |
| 0.062         | 22.0  | 638  | 0.1784          | 0.6137    | 0.6164 | 0.6151 | 0.9665   |
| 0.062         | 23.0  | 667  | 0.1730          | 0.6276    | 0.6466 | 0.6369 | 0.9678   |
| 0.062         | 24.0  | 696  | 0.1822          | 0.6076    | 0.6207 | 0.6141 | 0.9660   |
| 0.062         | 25.0  | 725  | 0.1820          | 0.6306    | 0.6034 | 0.6167 | 0.9678   |
| 0.062         | 26.0  | 754  | 0.1792          | 0.6083    | 0.6293 | 0.6186 | 0.9671   |
| 0.062         | 27.0  | 783  | 0.1810          | 0.6416    | 0.625  | 0.6332 | 0.9691   |
| 0.062         | 28.0  | 812  | 0.1800          | 0.6360    | 0.625  | 0.6304 | 0.9687   |
| 0.062         | 29.0  | 841  | 0.1811          | 0.6025    | 0.6336 | 0.6176 | 0.9660   |
| 0.062         | 30.0  | 870  | 0.1821          | 0.6074    | 0.6336 | 0.6203 | 0.9664   |
| 0.062         | 31.0  | 899  | 0.1825          | 0.6388    | 0.625  | 0.6318 | 0.9685   |
| 0.062         | 32.0  | 928  | 0.1830          | 0.64      | 0.6207 | 0.6302 | 0.9685   |


### Framework versions

- Transformers 4.28.1
- 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": "modelBsc", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

modelBsc
========


This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1830
* Precision: 0.64
* Recall: 0.6207
* F1: 0.6302
* Accuracy: 0.9685


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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32


### Training results



### Framework versions


* Transformers 4.28.1
* 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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 32### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3