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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/multi-train-distemist-dev-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: Rodrigo1771/multi-train-distemist-dev-ner
type: Rodrigo1771/multi-train-distemist-dev-ner
config: MultiTrainDisTEMISTDevNER
split: validation
args: MultiTrainDisTEMISTDevNER
metrics:
- name: Precision
type: precision
value: 0.32143181611701643
- name: Recall
type: recall
value: 0.8277959756668226
- name: F1
type: f1
value: 0.46305870034683594
- name: Accuracy
type: accuracy
value: 0.8559776451929613
---
<!-- 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/multi-train-distemist-dev-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9499
- Precision: 0.3214
- Recall: 0.8278
- F1: 0.4631
- Accuracy: 0.8560
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2596 | 0.9997 | 1701 | 0.4319 | 0.2617 | 0.7866 | 0.3927 | 0.8359 |
| 0.1853 | 2.0 | 3403 | 0.3841 | 0.3142 | 0.7829 | 0.4485 | 0.8645 |
| 0.1254 | 2.9997 | 5104 | 0.6410 | 0.3055 | 0.8088 | 0.4435 | 0.8436 |
| 0.0823 | 4.0 | 6806 | 0.7242 | 0.2964 | 0.8074 | 0.4336 | 0.8436 |
| 0.0597 | 4.9997 | 8507 | 0.7756 | 0.3133 | 0.7948 | 0.4495 | 0.8502 |
| 0.0446 | 6.0 | 10209 | 0.8561 | 0.3137 | 0.8037 | 0.4513 | 0.8483 |
| 0.0325 | 6.9997 | 11910 | 0.9499 | 0.3214 | 0.8278 | 0.4631 | 0.8560 |
| 0.022 | 8.0 | 13612 | 1.0452 | 0.3129 | 0.8222 | 0.4533 | 0.8510 |
| 0.017 | 8.9997 | 15313 | 1.1025 | 0.3133 | 0.8180 | 0.4531 | 0.8524 |
| 0.0135 | 9.9971 | 17010 | 1.1188 | 0.3145 | 0.8224 | 0.4550 | 0.8526 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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