Downloads · 30 days
8
15% of all-time downloads
nbbert_ED
yemen2016/nbbert_ED
nbbert_ED is a text classification model from yemen2016. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
52
Public
Parameters
178M
7.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors711 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-4.0
- Model type
- bert
- Access
- Public
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024
- SHA
- b744ba8c
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. -->
nbbert_ED
This model is a fine-tuned version of NbAiLab/nb-bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9955
- F1-score: 0.8361
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|---|---|---|---|---|
| No log | 1.0 | 69 | 0.6947 | 0.4209 |
| No log | 2.0 | 138 | 0.8251 | 0.6436 |
| No log | 3.0 | 207 | 0.6215 | 0.7587 |
| No log | 4.0 | 276 | 0.5942 | 0.7622 |
| No log | 5.0 | 345 | 0.6512 | 0.7622 |
| No log | 6.0 | 414 | 0.5853 | 0.7855 |
| No log | 7.0 | 483 | 1.1781 | 0.6619 |
| 0.4341 | 8.0 | 552 | 0.9684 | 0.7596 |
| 0.4341 | 9.0 | 621 | 0.8108 | 0.7951 |
| 0.4341 | 10.0 | 690 | 0.9732 | 0.7849 |
| 0.4341 | 11.0 | 759 | 0.8429 | 0.8276 |
| 0.4341 | 12.0 | 828 | 1.1912 | 0.7576 |
| 0.4341 | 13.0 | 897 | 1.0208 | 0.8115 |
| 0.4341 | 14.0 | 966 | 0.9234 | 0.8197 |
| 0.1528 | 15.0 | 1035 | 0.8931 | 0.8357 |
| 0.1528 | 16.0 | 1104 | 1.1005 | 0.8025 |
| 0.1528 | 17.0 | 1173 | 0.9808 | 0.8279 |
| 0.1528 | 18.0 | 1242 | 1.0438 | 0.8195 |
| 0.1528 | 19.0 | 1311 | 1.0193 | 0.8197 |
| 0.1528 | 20.0 | 1380 | 0.9955 | 0.8361 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- cc-by-4.0
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024