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# modelBsc5

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: 0.1546
- Precision: 0.5567
- Recall: 0.6075
- F1: 0.5810
- Accuracy: 0.9708

## 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   | 0.2697          | 0.0       | 0.0    | 0.0    | 0.9446   |
| No log        | 2.0   | 58   | 0.2357          | 0.0       | 0.0    | 0.0    | 0.9446   |
| No log        | 3.0   | 87   | 0.2176          | 0.0       | 0.0    | 0.0    | 0.9446   |
| No log        | 4.0   | 116  | 0.1889          | 0.0541    | 0.0108 | 0.0179 | 0.9406   |
| No log        | 5.0   | 145  | 0.1800          | 0.1613    | 0.0269 | 0.0461 | 0.9477   |
| No log        | 6.0   | 174  | 0.1625          | 0.2745    | 0.0753 | 0.1181 | 0.9532   |
| No log        | 7.0   | 203  | 0.1502          | 0.4306    | 0.1667 | 0.2403 | 0.9571   |
| No log        | 8.0   | 232  | 0.1426          | 0.3810    | 0.2581 | 0.3077 | 0.9576   |
| No log        | 9.0   | 261  | 0.1459          | 0.5586    | 0.3333 | 0.4175 | 0.9638   |
| No log        | 10.0  | 290  | 0.1288          | 0.5732    | 0.5054 | 0.5371 | 0.9636   |
| No log        | 11.0  | 319  | 0.1241          | 0.4769    | 0.5538 | 0.5124 | 0.9638   |
| No log        | 12.0  | 348  | 0.1282          | 0.5189    | 0.5161 | 0.5175 | 0.9664   |
| No log        | 13.0  | 377  | 0.1335          | 0.4232    | 0.6667 | 0.5177 | 0.9595   |
| No log        | 14.0  | 406  | 0.1314          | 0.5854    | 0.5161 | 0.5486 | 0.9693   |
| No log        | 15.0  | 435  | 0.1357          | 0.4772    | 0.6183 | 0.5386 | 0.9653   |
| No log        | 16.0  | 464  | 0.1382          | 0.4398    | 0.6290 | 0.5177 | 0.9638   |
| No log        | 17.0  | 493  | 0.1362          | 0.5634    | 0.6452 | 0.6015 | 0.9705   |
| 0.1141        | 18.0  | 522  | 0.1466          | 0.5       | 0.6505 | 0.5654 | 0.9669   |
| 0.1141        | 19.0  | 551  | 0.1497          | 0.5441    | 0.5968 | 0.5692 | 0.9703   |
| 0.1141        | 20.0  | 580  | 0.1375          | 0.5520    | 0.6559 | 0.5995 | 0.9700   |
| 0.1141        | 21.0  | 609  | 0.1373          | 0.5707    | 0.6290 | 0.5985 | 0.9722   |
| 0.1141        | 22.0  | 638  | 0.1490          | 0.5777    | 0.6398 | 0.6071 | 0.9710   |
| 0.1141        | 23.0  | 667  | 0.1550          | 0.5314    | 0.6828 | 0.5976 | 0.9679   |
| 0.1141        | 24.0  | 696  | 0.1506          | 0.5397    | 0.6935 | 0.6071 | 0.9679   |
| 0.1141        | 25.0  | 725  | 0.1528          | 0.5346    | 0.6237 | 0.5757 | 0.9703   |
| 0.1141        | 26.0  | 754  | 0.1503          | 0.5764    | 0.6290 | 0.6015 | 0.9715   |
| 0.1141        | 27.0  | 783  | 0.1446          | 0.5767    | 0.5860 | 0.5813 | 0.9722   |
| 0.1141        | 28.0  | 812  | 0.1486          | 0.5377    | 0.6129 | 0.5729 | 0.9701   |
| 0.1141        | 29.0  | 841  | 0.1538          | 0.5577    | 0.6237 | 0.5888 | 0.9703   |
| 0.1141        | 30.0  | 870  | 0.1543          | 0.5545    | 0.6022 | 0.5773 | 0.9701   |
| 0.1141        | 31.0  | 899  | 0.1551          | 0.5517    | 0.6022 | 0.5758 | 0.9708   |
| 0.1141        | 32.0  | 928  | 0.1546          | 0.5567    | 0.6075 | 0.5810 | 0.9708   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "modelBsc5", "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 

modelBsc5
=========


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: 0.1546
* Precision: 0.5567
* Recall: 0.6075
* F1: 0.5810
* Accuracy: 0.9708


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 2.12.0
* 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 2.12.0
* 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 2.12.0
* Tokenizers 0.13.3