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# 25

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: 0.1790
- Precision: 0.5417
- Recall: 0.5617
- F1: 0.5515
- Accuracy: 0.9711

## 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: 5.25e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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   | 0.2546          | 0.0       | 0.0    | 0.0    | 0.9475   |
| No log        | 2.0   | 58   | 0.2270          | 0.0       | 0.0    | 0.0    | 0.9475   |
| No log        | 3.0   | 87   | 0.2095          | 0.0       | 0.0    | 0.0    | 0.9475   |
| No log        | 4.0   | 116  | 0.1961          | 0.0       | 0.0    | 0.0    | 0.9462   |
| No log        | 5.0   | 145  | 0.1666          | 0.1786    | 0.0309 | 0.0526 | 0.9537   |
| No log        | 6.0   | 174  | 0.1471          | 0.5385    | 0.1296 | 0.2090 | 0.9606   |
| No log        | 7.0   | 203  | 0.1391          | 0.4085    | 0.1790 | 0.2489 | 0.9628   |
| No log        | 8.0   | 232  | 0.1338          | 0.4576    | 0.3333 | 0.3857 | 0.9653   |
| No log        | 9.0   | 261  | 0.1359          | 0.4       | 0.3704 | 0.3846 | 0.9656   |
| No log        | 10.0  | 290  | 0.1429          | 0.47      | 0.2901 | 0.3588 | 0.9675   |
| No log        | 11.0  | 319  | 0.1299          | 0.4872    | 0.4691 | 0.4780 | 0.9692   |
| No log        | 12.0  | 348  | 0.1380          | 0.3938    | 0.5494 | 0.4588 | 0.9625   |
| No log        | 13.0  | 377  | 0.1426          | 0.4970    | 0.5123 | 0.5046 | 0.9696   |
| No log        | 14.0  | 406  | 0.1492          | 0.4378    | 0.5432 | 0.4848 | 0.9651   |
| No log        | 15.0  | 435  | 0.1460          | 0.4286    | 0.5370 | 0.4767 | 0.9656   |
| No log        | 16.0  | 464  | 0.1479          | 0.5380    | 0.5247 | 0.5312 | 0.9699   |
| No log        | 17.0  | 493  | 0.1558          | 0.4673    | 0.5741 | 0.5152 | 0.9679   |
| 0.1212        | 18.0  | 522  | 0.1617          | 0.5442    | 0.4938 | 0.5178 | 0.9712   |
| 0.1212        | 19.0  | 551  | 0.1672          | 0.4686    | 0.5988 | 0.5257 | 0.9662   |
| 0.1212        | 20.0  | 580  | 0.1634          | 0.4943    | 0.5309 | 0.5119 | 0.9692   |
| 0.1212        | 21.0  | 609  | 0.1673          | 0.5054    | 0.5802 | 0.5402 | 0.9684   |
| 0.1212        | 22.0  | 638  | 0.1677          | 0.5130    | 0.4877 | 0.5    | 0.9703   |
| 0.1212        | 23.0  | 667  | 0.1628          | 0.5687    | 0.5617 | 0.5652 | 0.9720   |
| 0.1212        | 24.0  | 696  | 0.1704          | 0.4865    | 0.5556 | 0.5187 | 0.9692   |
| 0.1212        | 25.0  | 725  | 0.1704          | 0.5660    | 0.5556 | 0.5607 | 0.9720   |
| 0.1212        | 26.0  | 754  | 0.1710          | 0.5644    | 0.5679 | 0.5662 | 0.9718   |
| 0.1212        | 27.0  | 783  | 0.1757          | 0.5380    | 0.5679 | 0.5526 | 0.9709   |
| 0.1212        | 28.0  | 812  | 0.1767          | 0.5112    | 0.5617 | 0.5353 | 0.9703   |
| 0.1212        | 29.0  | 841  | 0.1745          | 0.5588    | 0.5864 | 0.5723 | 0.9714   |
| 0.1212        | 30.0  | 870  | 0.1770          | 0.5515    | 0.5617 | 0.5566 | 0.9711   |
| 0.1212        | 31.0  | 899  | 0.1789          | 0.5417    | 0.5617 | 0.5515 | 0.9711   |
| 0.1212        | 32.0  | 928  | 0.1790          | 0.5417    | 0.5617 | 0.5515 | 0.9711   |


### 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": "25", "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 

25
==


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: 0.1790
* Precision: 0.5417
* Recall: 0.5617
* F1: 0.5515
* Accuracy: 0.9711


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: 5.25e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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: 5.25e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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: 5.25e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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