Downloads · 30 days
6
10% of all-time downloads
bsc-bio-ehr-es-symptemist-fasttext-85-ner
Rodrigo1771/bsc-bio-ehr-es-symptemist-fasttext-85-ner
bsc-bio-ehr-es-symptemist-fasttext-85-ner is a token classification model from Rodrigo1771. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
58
Public
Parameters
124M
5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors496 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024
- SHA
- 4ee5e701
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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 on the Rodrigo1771/symptemist-fasttext-85-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.2808
- Precision: 0.6529
- Recall: 0.7115
- F1: 0.6810
- Accuracy: 0.9473
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 | 171 | 0.1502 | 0.5421 | 0.6765 | 0.6019 | 0.9458 |
| No log | 2.0 | 342 | 0.1539 | 0.5958 | 0.6793 | 0.6348 | 0.9468 |
| 0.1273 | 3.0 | 513 | 0.1838 | 0.6326 | 0.7077 | 0.6680 | 0.9468 |
| 0.1273 | 4.0 | 684 | 0.2018 | 0.6322 | 0.7121 | 0.6698 | 0.9466 |
| 0.1273 | 5.0 | 855 | 0.2153 | 0.6441 | 0.7192 | 0.6796 | 0.9465 |
| 0.0234 | 6.0 | 1026 | 0.2498 | 0.6461 | 0.7006 | 0.6723 | 0.9470 |
| 0.0234 | 7.0 | 1197 | 0.2653 | 0.6362 | 0.7209 | 0.6759 | 0.9462 |
| 0.0234 | 8.0 | 1368 | 0.2808 | 0.6529 | 0.7115 | 0.6810 | 0.9473 |
| 0.0082 | 9.0 | 1539 | 0.2917 | 0.6458 | 0.7115 | 0.6771 | 0.9467 |
| 0.0082 | 10.0 | 1710 | 0.2930 | 0.6548 | 0.7072 | 0.6800 | 0.9481 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024