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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-distemist-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-distemist-dev-85-ner
type: Rodrigo1771/combined-train-distemist-dev-85-ner
config: CombinedTrainDisTEMISTDevNER
split: validation
args: CombinedTrainDisTEMISTDevNER
metrics:
- name: Precision
type: precision
value: 0.3152508603513856
- name: Recall
type: recall
value: 0.8144595226953674
- name: F1
type: f1
value: 0.45455732567249935
- name: Accuracy
type: accuracy
value: 0.8564886649182308
---
<!-- 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-distemist-dev-85-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7006
- Precision: 0.3153
- Recall: 0.8145
- F1: 0.4546
- Accuracy: 0.8565
## 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 | 0.4772 | 0.2725 | 0.8074 | 0.4075 | 0.8443 |
| 0.1619 | 2.0 | 1082 | 0.4584 | 0.3041 | 0.7941 | 0.4398 | 0.8553 |
| 0.11 | 3.0 | 1623 | 0.6447 | 0.2976 | 0.8000 | 0.4338 | 0.8435 |
| 0.0764 | 4.0 | 2164 | 0.7413 | 0.2896 | 0.7871 | 0.4234 | 0.8399 |
| 0.0567 | 5.0 | 2705 | 0.7006 | 0.3153 | 0.8145 | 0.4546 | 0.8565 |
| 0.0428 | 6.0 | 3246 | 0.8112 | 0.3071 | 0.8210 | 0.4470 | 0.8504 |
| 0.0332 | 7.0 | 3787 | 0.9046 | 0.3114 | 0.8070 | 0.4494 | 0.8533 |
| 0.0257 | 8.0 | 4328 | 0.9723 | 0.3060 | 0.8109 | 0.4444 | 0.8482 |
| 0.022 | 9.0 | 4869 | 1.0028 | 0.3087 | 0.8077 | 0.4467 | 0.8502 |
| 0.0181 | 10.0 | 5410 | 1.0023 | 0.3116 | 0.8119 | 0.4504 | 0.8533 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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