Downloads · 30 days
11
18% of all-time downloads
bsc-bio-ehr-es-drugtemist-ner
Rodrigo1771/bsc-bio-ehr-es-drugtemist-ner
bsc-bio-ehr-es-drugtemist-ner is a token classification model from Rodrigo1771. Use it when you need labels on individual words, such as names. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
62
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
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024
- SHA
- 2460aeea
Try a prompt
Base models
Datasets
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/drugtemist-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0055
- Precision: 0.9395
- Recall: 0.9559
- F1: 0.9476
- Accuracy: 0.9990
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 | 0.0050 | 0.9251 | 0.8971 | 0.9109 | 0.9982 |
| 0.0196 | 2.0 | 851 | 0.0038 | 0.9400 | 0.9219 | 0.9309 | 0.9988 |
| 0.0031 | 2.9988 | 1276 | 0.0035 | 0.9335 | 0.9292 | 0.9314 | 0.9988 |
| 0.0017 | 4.0 | 1702 | 0.0041 | 0.9119 | 0.9605 | 0.9355 | 0.9988 |
| 0.0009 | 4.9988 | 2127 | 0.0047 | 0.9393 | 0.9522 | 0.9457 | 0.9989 |
| 0.0004 | 6.0 | 2553 | 0.0055 | 0.9413 | 0.9430 | 0.9421 | 0.9989 |
| 0.0004 | 6.9988 | 2978 | 0.0054 | 0.9320 | 0.9577 | 0.9447 | 0.9989 |
| 0.0003 | 8.0 | 3404 | 0.0053 | 0.9346 | 0.9596 | 0.9469 | 0.9989 |
| 0.0002 | 8.9988 | 3829 | 0.0057 | 0.9385 | 0.9531 | 0.9457 | 0.9989 |
| 0.0001 | 9.9882 | 4250 | 0.0055 | 0.9395 | 0.9559 | 0.9476 | 0.9990 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Token Classification
- Type
- roberta
- License
- apache-2.0
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024