Downloads · 30 days
7
17% of all-time downloads
Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-tokenizer-adapted-spanmask-lr_2.16
CeLLaTe-ner-2class-pubmedbert-tapt-tokenizer-adapted-spanmask-lr_2.16 is a token classification model from Mardiyyah. 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. --
Downloads · 30 days
7
17% of all-time downloads
All-time downloads
41
Public
Parameters
110M
442 MB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors442 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of Mardiyyah/CeLLaTe-tapt-pubmedbert-tokenizer-adapted-spanmask on the OTAR3088/CeLLaTe-ner-2class-iob_final dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Micro F1 | Weighted F1 | Macro F1 | Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| 0.2892 | 1.0 | 263 | 0.0692 | 0.5629 | 0.6542 | 0.6051 | 0.6075 | 0.6199 | 0.9759 |
| 0.0413 | 2.0 | 526 | 0.0550 | 0.7616 | 0.7126 | 0.7363 | 0.7363 | 0.7451 | 0.9832 |
| 0.026 | 3.0 | 789 | 0.0601 | 0.7599 | 0.7156 | 0.7371 | 0.7373 | 0.7447 | 0.9830 |
| 0.018 | 4.0 | 1052 | 0.0711 | 0.7861 | 0.7029 | 0.7422 | 0.7422 | 0.7481 | 0.9829 |
| 0.013 | 5.0 | 1315 | 0.0725 | 0.8024 | 0.7348 | 0.7671 | 0.7668 | 0.7754 | 0.9841 |
| 0.0105 | 6.0 | 1578 | 0.0767 | 0.7937 | 0.7288 | 0.7599 | 0.7597 | 0.7663 | 0.9839 |
| 0.0075 | 7.0 | 1841 | 0.0791 | 0.7409 | 0.7565 | 0.7486 | 0.7486 | 0.7490 | 0.9831 |
| 0.0065 | 8.0 | 2104 | 0.0835 | 0.7658 | 0.7511 | 0.7583 | 0.7584 | 0.7656 | 0.9836 |
| 0.0054 | 9.0 | 2367 | 0.0838 | 0.7370 | 0.7649 | 0.7507 | 0.7512 | 0.7607 | 0.9832 |
| 0.0043 | 10.0 | 2630 | 0.0954 | 0.7796 | 0.7318 | 0.7550 | 0.7550 | 0.7616 | 0.9838 |