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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- shared-task
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bsc-bio-ehr-es-finetuned-ner-1
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: shared-task
type: shared-task
config: Shared
split: validation
args: Shared
metrics:
- name: Precision
type: precision
value: 0.28507462686567164
- name: Recall
type: recall
value: 0.3560111835973905
- name: F1
type: f1
value: 0.3166183174471612
- name: Accuracy
type: accuracy
value: 0.8444321635810997
---
<!-- 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. -->
# bsc-bio-ehr-es-finetuned-ner-1
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 shared-task dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6021
- Precision: 0.2851
- Recall: 0.3560
- F1: 0.3166
- Accuracy: 0.8444
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 59 | 0.6644 | 0.2234 | 0.2600 | 0.2403 | 0.8198 |
| No log | 2.0 | 118 | 0.5786 | 0.1997 | 0.2507 | 0.2223 | 0.8331 |
| No log | 3.0 | 177 | 0.6083 | 0.2732 | 0.3187 | 0.2942 | 0.8379 |
| No log | 4.0 | 236 | 0.6032 | 0.2855 | 0.3486 | 0.3139 | 0.8366 |
| No log | 5.0 | 295 | 0.6021 | 0.2851 | 0.3560 | 0.3166 | 0.8444 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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