output
This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the Rodrigo1771/symptemist-fasttext-75-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.3374
- Precision: 0.6784
- Recall: 0.7159
- F1: 0.6967
- Accuracy: 0.9490
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 | 258 | 0.1517 | 0.6354 | 0.6448 | 0.6400 | 0.9488 |
0.1357 | 2.0 | 516 | 0.2025 | 0.6306 | 0.7137 | 0.6696 | 0.9460 |
0.1357 | 3.0 | 774 | 0.2294 | 0.6649 | 0.7039 | 0.6839 | 0.9496 |
0.0238 | 4.0 | 1032 | 0.2818 | 0.6689 | 0.7066 | 0.6873 | 0.9492 |
0.0238 | 5.0 | 1290 | 0.2762 | 0.6528 | 0.7039 | 0.6774 | 0.9487 |
0.0081 | 6.0 | 1548 | 0.2938 | 0.6663 | 0.7203 | 0.6923 | 0.9484 |
0.0081 | 7.0 | 1806 | 0.3145 | 0.6789 | 0.7001 | 0.6893 | 0.9499 |
0.0039 | 8.0 | 2064 | 0.3267 | 0.6686 | 0.7055 | 0.6866 | 0.9491 |
0.0039 | 9.0 | 2322 | 0.3374 | 0.6784 | 0.7159 | 0.6967 | 0.9490 |
0.0021 | 10.0 | 2580 | 0.3400 | 0.6827 | 0.7077 | 0.6950 | 0.9495 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 63
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for Rodrigo1771/bsc-bio-ehr-es-symptemist-fasttext-75-ner
Base model
PlanTL-GOB-ES/bsc-bio-ehr-esDataset used to train Rodrigo1771/bsc-bio-ehr-es-symptemist-fasttext-75-ner
Evaluation results
- Precision on Rodrigo1771/symptemist-fasttext-75-nervalidation set self-reported0.678
- Recall on Rodrigo1771/symptemist-fasttext-75-nervalidation set self-reported0.716
- F1 on Rodrigo1771/symptemist-fasttext-75-nervalidation set self-reported0.697
- Accuracy on Rodrigo1771/symptemist-fasttext-75-nervalidation set self-reported0.949