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---
license: apache-2.0
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
tags:
- token-classification
- generated_from_trainer
datasets:
- Rodrigo1771/distemist-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: Rodrigo1771/distemist-ner
type: Rodrigo1771/distemist-ner
config: DisTEMIST NER
split: validation
args: DisTEMIST NER
metrics:
- name: Precision
type: precision
value: 0.7938948817994033
- name: Recall
type: recall
value: 0.8093121197941039
- name: F1
type: f1
value: 0.8015293708724366
- name: Accuracy
type: accuracy
value: 0.9767668584453568
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output
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 the Rodrigo1771/distemist-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1294
- Precision: 0.7939
- Recall: 0.8093
- F1: 0.8015
- Accuracy: 0.9768
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.9988 | 425 | 0.0738 | 0.7233 | 0.7866 | 0.7536 | 0.9733 |
| 0.0996 | 2.0 | 851 | 0.0787 | 0.7364 | 0.8065 | 0.7698 | 0.9743 |
| 0.0458 | 2.9988 | 1276 | 0.0788 | 0.7715 | 0.8154 | 0.7929 | 0.9759 |
| 0.0279 | 4.0 | 1702 | 0.0922 | 0.7754 | 0.8112 | 0.7929 | 0.9757 |
| 0.0169 | 4.9988 | 2127 | 0.0994 | 0.7585 | 0.8163 | 0.7863 | 0.9744 |
| 0.0114 | 6.0 | 2553 | 0.1080 | 0.7766 | 0.8058 | 0.7909 | 0.9765 |
| 0.0114 | 6.9988 | 2978 | 0.1166 | 0.7792 | 0.8100 | 0.7943 | 0.9760 |
| 0.0079 | 8.0 | 3404 | 0.1294 | 0.7939 | 0.8093 | 0.8015 | 0.9768 |
| 0.0053 | 8.9988 | 3829 | 0.1340 | 0.7876 | 0.8105 | 0.7989 | 0.9766 |
| 0.0038 | 9.9882 | 4250 | 0.1367 | 0.7882 | 0.8098 | 0.7988 | 0.9767 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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