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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/combined-train-distemist-dev-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-ner
type: Rodrigo1771/combined-train-distemist-dev-ner
config: CombinedTrainDisTEMISTDevNER
split: validation
args: CombinedTrainDisTEMISTDevNER
metrics:
- name: Precision
type: precision
value: 0.32197630636422075
- name: Recall
type: recall
value: 0.8203088441740758
- name: F1
type: f1
value: 0.4624414693662204
- name: Accuracy
type: accuracy
value: 0.8601754843670617
---
<!-- 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-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6266
- Precision: 0.3220
- Recall: 0.8203
- F1: 0.4624
- Accuracy: 0.8602
## 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 | 0.9988 | 425 | 0.3834 | 0.2920 | 0.7819 | 0.4252 | 0.8517 |
| 0.3349 | 2.0 | 851 | 0.5730 | 0.2681 | 0.8070 | 0.4025 | 0.8221 |
| 0.1788 | 2.9988 | 1276 | 0.5796 | 0.2848 | 0.8009 | 0.4202 | 0.8338 |
| 0.1227 | 4.0 | 1702 | 0.6591 | 0.2996 | 0.8109 | 0.4376 | 0.8388 |
| 0.0856 | 4.9988 | 2127 | 0.6266 | 0.3220 | 0.8203 | 0.4624 | 0.8602 |
| 0.0597 | 6.0 | 2553 | 0.7859 | 0.3075 | 0.8112 | 0.4460 | 0.8476 |
| 0.0597 | 6.9988 | 2978 | 0.8297 | 0.3137 | 0.8166 | 0.4532 | 0.8508 |
| 0.0458 | 8.0 | 3404 | 0.8468 | 0.3135 | 0.8205 | 0.4536 | 0.8532 |
| 0.0343 | 8.9988 | 3829 | 0.9241 | 0.3085 | 0.8182 | 0.4481 | 0.8494 |
| 0.0292 | 9.9882 | 4250 | 0.9384 | 0.3100 | 0.8163 | 0.4494 | 0.8499 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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