Downloads · 30 days
13
7% of all-time downloads
Medicamentos
FELIPE960407/Medicamentos
Medicamentos is a text classification model from FELIPE960407. Use it when you need a label for a piece of text. 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
180
Public
Parameters
67.4M
3.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors270 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- May 17, 2026
- Updated
- May 17, 2026
- SHA
- f283229d
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. -->
Medicamentos
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5049
- Accuracy: 0.5727
- F1 Macro: 0.4143
- F1 Weighted: 0.4778
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 6.1569 | 1.0 | 602 | 5.6599 | 0.2205 | 0.0653 | 0.1279 |
| 5.5160 | 2.0 | 1204 | 4.8245 | 0.3405 | 0.1530 | 0.2332 |
| 4.8671 | 3.0 | 1806 | 4.1690 | 0.4012 | 0.2098 | 0.2885 |
| 4.3018 | 4.0 | 2408 | 3.6654 | 0.4464 | 0.2656 | 0.3353 |
| 3.4892 | 5.0 | 3010 | 3.2754 | 0.4921 | 0.3173 | 0.3813 |
| 3.1833 | 6.0 | 3612 | 2.9888 | 0.5170 | 0.3461 | 0.4113 |
| 2.9711 | 7.0 | 4214 | 2.7712 | 0.5390 | 0.3757 | 0.4368 |
| 2.7915 | 8.0 | 4816 | 2.6280 | 0.5519 | 0.3906 | 0.4517 |
| 2.6485 | 9.0 | 5418 | 2.5342 | 0.5631 | 0.4045 | 0.4657 |
| 2.5247 | 10.0 | 6020 | 2.5049 | 0.5727 | 0.4143 | 0.4778 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 17, 2026
- Updated
- May 17, 2026