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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/symptemist-75-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: Rodrigo1771/symptemist-75-ner
type: Rodrigo1771/symptemist-75-ner
config: SympTEMIST NER
split: validation
args: SympTEMIST NER
metrics:
- name: Precision
type: precision
value: 0.6896
- name: Recall
type: recall
value: 0.7077175697865353
- name: F1
type: f1
value: 0.6985413290113451
- name: Accuracy
type: accuracy
value: 0.9496936058263018
---
<!-- 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/symptemist-75-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3089
- Precision: 0.6896
- Recall: 0.7077
- F1: 0.6985
- Accuracy: 0.9497
## 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 | 1.0 | 248 | 0.1649 | 0.5942 | 0.6820 | 0.6351 | 0.9478 |
| No log | 2.0 | 496 | 0.1815 | 0.6558 | 0.6705 | 0.6631 | 0.9476 |
| 0.134 | 3.0 | 744 | 0.2111 | 0.6651 | 0.6979 | 0.6811 | 0.9492 |
| 0.134 | 4.0 | 992 | 0.2523 | 0.6692 | 0.7121 | 0.6900 | 0.9488 |
| 0.026 | 5.0 | 1240 | 0.2771 | 0.6584 | 0.7132 | 0.6847 | 0.9491 |
| 0.026 | 6.0 | 1488 | 0.2968 | 0.6668 | 0.7165 | 0.6908 | 0.9486 |
| 0.0084 | 7.0 | 1736 | 0.3089 | 0.6896 | 0.7077 | 0.6985 | 0.9497 |
| 0.0084 | 8.0 | 1984 | 0.3188 | 0.6825 | 0.7072 | 0.6946 | 0.9499 |
| 0.0042 | 9.0 | 2232 | 0.3296 | 0.6809 | 0.7159 | 0.6980 | 0.9495 |
| 0.0042 | 10.0 | 2480 | 0.3328 | 0.6814 | 0.7165 | 0.6985 | 0.9499 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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