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# testlink-class-3

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: 0.1443
- Precision: 0.5833
- Recall: 0.6550
- F1: 0.6171
- Accuracy: 0.9730

## 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: 7.5e-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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2830          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 2.0   | 58   | 0.2789          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 3.0   | 87   | 0.2388          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 4.0   | 116  | 0.2080          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 5.0   | 145  | 0.2335          | 0.0167    | 0.0058 | 0.0087 | 0.9322   |
| No log        | 6.0   | 174  | 0.1889          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 7.0   | 203  | 0.1553          | 0.3469    | 0.1988 | 0.2528 | 0.9506   |
| No log        | 8.0   | 232  | 0.1491          | 0.5       | 0.2339 | 0.3187 | 0.9576   |
| No log        | 9.0   | 261  | 0.1604          | 0.4872    | 0.2222 | 0.3052 | 0.9605   |
| No log        | 10.0  | 290  | 0.1347          | 0.4733    | 0.3626 | 0.4106 | 0.9587   |
| No log        | 11.0  | 319  | 0.1391          | 0.5165    | 0.2749 | 0.3588 | 0.9605   |
| No log        | 12.0  | 348  | 0.1392          | 0.4848    | 0.3743 | 0.4224 | 0.9633   |
| No log        | 13.0  | 377  | 0.1306          | 0.4706    | 0.3743 | 0.4169 | 0.9636   |
| No log        | 14.0  | 406  | 0.1382          | 0.4774    | 0.4327 | 0.4540 | 0.9642   |
| No log        | 15.0  | 435  | 0.1368          | 0.4734    | 0.5205 | 0.4958 | 0.9655   |
| No log        | 16.0  | 464  | 0.1316          | 0.5052    | 0.5731 | 0.5370 | 0.9666   |
| No log        | 17.0  | 493  | 0.1333          | 0.4852    | 0.6725 | 0.5637 | 0.9660   |
| 0.1607        | 18.0  | 522  | 0.1379          | 0.56      | 0.5731 | 0.5665 | 0.9695   |
| 0.1607        | 19.0  | 551  | 0.1534          | 0.5941    | 0.5906 | 0.5924 | 0.9706   |
| 0.1607        | 20.0  | 580  | 0.1294          | 0.5606    | 0.6491 | 0.6016 | 0.9712   |
| 0.1607        | 21.0  | 609  | 0.1403          | 0.5231    | 0.6608 | 0.5840 | 0.9704   |
| 0.1607        | 22.0  | 638  | 0.1429          | 0.6044    | 0.6433 | 0.6232 | 0.9719   |
| 0.1607        | 23.0  | 667  | 0.1411          | 0.5825    | 0.6608 | 0.6192 | 0.9719   |
| 0.1607        | 24.0  | 696  | 0.1339          | 0.5631    | 0.6784 | 0.6154 | 0.9708   |
| 0.1607        | 25.0  | 725  | 0.1345          | 0.5825    | 0.6608 | 0.6192 | 0.9721   |
| 0.1607        | 26.0  | 754  | 0.1464          | 0.5833    | 0.6550 | 0.6171 | 0.9717   |
| 0.1607        | 27.0  | 783  | 0.1403          | 0.5672    | 0.6667 | 0.6129 | 0.9715   |
| 0.1607        | 28.0  | 812  | 0.1445          | 0.5934    | 0.6316 | 0.6119 | 0.9725   |
| 0.1607        | 29.0  | 841  | 0.1433          | 0.5588    | 0.6667 | 0.608  | 0.9715   |
| 0.1607        | 30.0  | 870  | 0.1443          | 0.5833    | 0.6550 | 0.6171 | 0.9730   |


### 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": "testlink-class-3", "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 

testlink-class-3
================


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: 0.1443
* Precision: 0.5833
* Recall: 0.6550
* F1: 0.6171
* Accuracy: 0.9730


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: 7.5e-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: 30


### 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: 7.5e-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: 30 ### 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: 7.5e-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: 30 ### Training results ### Framework versions


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