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# clinico-bsc-bio-ehr-es-longformer

This model is a fine-tuned version of [PlanTL-GOB-ES/longformer-base-4096-bne-es](https://huggingface.co/PlanTL-GOB-ES/longformer-base-4096-bne-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6428
- Precision: 0.3546
- Recall: 0.5613
- F1: 0.4346
- Accuracy: 0.8453

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 196  | 0.6951          | 0.1691    | 0.2915 | 0.2141 | 0.7928   |
| No log        | 2.0   | 392  | 0.5699          | 0.2181    | 0.3708 | 0.2746 | 0.8210   |
| 0.7641        | 3.0   | 588  | 0.5545          | 0.2822    | 0.4736 | 0.3536 | 0.8287   |
| 0.7641        | 4.0   | 784  | 0.5516          | 0.2947    | 0.4915 | 0.3685 | 0.8421   |
| 0.7641        | 5.0   | 980  | 0.6118          | 0.3314    | 0.5368 | 0.4098 | 0.8338   |
| 0.3503        | 6.0   | 1176 | 0.6115          | 0.3391    | 0.5396 | 0.4165 | 0.8389   |
| 0.3503        | 7.0   | 1372 | 0.6407          | 0.3362    | 0.5509 | 0.4176 | 0.8377   |
| 0.2184        | 8.0   | 1568 | 0.6300          | 0.3312    | 0.55   | 0.4135 | 0.8380   |
| 0.2184        | 9.0   | 1764 | 0.6393          | 0.3646    | 0.5566 | 0.4406 | 0.8451   |
| 0.2184        | 10.0  | 1960 | 0.6428          | 0.3546    | 0.5613 | 0.4346 | 0.8453   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "clinico-bsc-bio-ehr-es-longformer", "results": []}]}
transformers pytorch longformer token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #longformer #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

clinico-bsc-bio-ehr-es-longformer
=================================


This model is a fine-tuned version of PlanTL-GOB-ES/longformer-base-4096-bne-es on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6428
* Precision: 0.3546
* Recall: 0.5613
* F1: 0.4346
* Accuracy: 0.8453


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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #longformer #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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #longformer #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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3