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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/cantemist-85-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: Rodrigo1771/cantemist-85-ner
type: Rodrigo1771/cantemist-85-ner
config: CantemistNer
split: validation
args: CantemistNer
metrics:
- name: Precision
type: precision
value: 0.8399232245681382
- name: Recall
type: recall
value: 0.8617565970854667
- name: F1
type: f1
value: 0.8506998444790046
- name: Accuracy
type: accuracy
value: 0.9916544445403043
---
<!-- 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/cantemist-85-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0496
- Precision: 0.8399
- Recall: 0.8618
- F1: 0.8507
- Accuracy: 0.9917
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0542 | 1.0 | 511 | 0.0271 | 0.7485 | 0.7972 | 0.7721 | 0.9895 |
| 0.0184 | 2.0 | 1022 | 0.0277 | 0.7897 | 0.8519 | 0.8196 | 0.9906 |
| 0.0103 | 3.0 | 1533 | 0.0305 | 0.8238 | 0.8488 | 0.8361 | 0.9914 |
| 0.0058 | 4.0 | 2044 | 0.0320 | 0.8197 | 0.8539 | 0.8364 | 0.9913 |
| 0.0041 | 5.0 | 2555 | 0.0374 | 0.8397 | 0.8417 | 0.8407 | 0.9917 |
| 0.0026 | 6.0 | 3066 | 0.0427 | 0.8368 | 0.8503 | 0.8435 | 0.9917 |
| 0.0015 | 7.0 | 3577 | 0.0451 | 0.8207 | 0.8598 | 0.8398 | 0.9912 |
| 0.0013 | 8.0 | 4088 | 0.0448 | 0.8318 | 0.8629 | 0.8471 | 0.9916 |
| 0.0007 | 9.0 | 4599 | 0.0496 | 0.8399 | 0.8618 | 0.8507 | 0.9917 |
| 0.0006 | 10.0 | 5110 | 0.0503 | 0.8399 | 0.8618 | 0.8507 | 0.9916 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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