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---
library_name: transformers
license: apache-2.0
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
tags:
- token-classification
- generated_from_trainer
datasets:
- Rodrigo1771/combined-train-drugtemist-dev-85-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: Rodrigo1771/combined-train-drugtemist-dev-85-ner
type: Rodrigo1771/combined-train-drugtemist-dev-85-ner
config: CombinedTrainDrugTEMISTDevNER
split: validation
args: CombinedTrainDrugTEMISTDevNER
metrics:
- name: Precision
type: precision
value: 0.09400470929179497
- name: Recall
type: recall
value: 0.9540441176470589
- name: F1
type: f1
value: 0.17114591920857378
- name: Accuracy
type: accuracy
value: 0.7890274211487498
---
<!-- 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/combined-train-drugtemist-dev-85-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1806
- Precision: 0.0940
- Recall: 0.9540
- F1: 0.1711
- Accuracy: 0.7890
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3191 | 1.0 | 541 | 0.8151 | 0.0825 | 0.9605 | 0.1520 | 0.7763 |
| 0.1619 | 2.0 | 1082 | 0.8332 | 0.0922 | 0.9458 | 0.168 | 0.7901 |
| 0.11 | 3.0 | 1623 | 1.1094 | 0.0899 | 0.9494 | 0.1643 | 0.7738 |
| 0.0764 | 4.0 | 2164 | 1.1206 | 0.0885 | 0.9449 | 0.1618 | 0.7740 |
| 0.0567 | 5.0 | 2705 | 1.1806 | 0.0940 | 0.9540 | 0.1711 | 0.7890 |
| 0.0428 | 6.0 | 3246 | 1.3138 | 0.0901 | 0.9458 | 0.1645 | 0.7827 |
| 0.0332 | 7.0 | 3787 | 1.4009 | 0.0922 | 0.9384 | 0.1679 | 0.7874 |
| 0.0257 | 8.0 | 4328 | 1.5611 | 0.0904 | 0.9412 | 0.1650 | 0.7791 |
| 0.022 | 9.0 | 4869 | 1.5934 | 0.0921 | 0.9467 | 0.1679 | 0.7835 |
| 0.0181 | 10.0 | 5410 | 1.6103 | 0.0922 | 0.9439 | 0.1680 | 0.7863 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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