Downloads · 30 days
25
30% of all-time downloads
Mardiyyah/CeLLaTe-tapt-pubmedbert-tokenizer-adapted_v2
CeLLaTe-tapt-pubmedbert-tokenizer-adapted_v2 is a fill-mask model from Mardiyyah. Use it when you need the model to fill a missing word. 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
25
30% of all-time downloads
All-time downloads
84
Public
Parameters
110M
1.8 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors438 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on the Mardiyyah/TAPT_CeLLaTe2.0 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 | Accuracy | Perplexity |
|---|---|---|---|---|---|
| 1.2084 | 1.0 | 14 | 1.0521 | 0.7681 | 2.8636 |
| 1.1946 | 2.0 | 28 | 1.0386 | 0.7696 | 2.8253 |
| 1.1586 | 3.0 | 42 | 1.0498 | 0.7687 | 2.8572 |
| 1.1324 | 4.0 | 56 | 1.0643 | 0.7652 | 2.8989 |
| 1.155 | 5.0 | 70 | 1.0055 | 0.7768 | 2.7334 |
| 1.1254 | 6.0 | 84 | 0.9817 | 0.7778 | 2.6691 |
| 1.1211 | 7.0 | 98 | 1.0599 | 0.7684 | 2.8862 |
| 1.0968 | 8.0 | 112 | 1.0617 | 0.7659 | 2.8912 |
| 1.0885 | 9.0 | 126 | 1.0601 | 0.7627 | 2.8868 |
| 1.0577 | 10.0 | 140 | 1.0537 | 0.7705 | 2.8683 |
| 1.0454 | 11.0 | 154 | 1.0260 | 0.7684 | 2.7898 |