Downloads · 30 days
4
9% of all-time downloads
model_compleet_wie_mask
svitse/model_compleet_wie_mask
model_compleet_wie_mask is a text classification model from svitse. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
46
Public
Parameters
109M
873 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors437 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 27, 2024
- Updated
- Feb 28, 2024
- SHA
- c8f8381b
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. -->
model_compleet_wie_mask
This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3972
- Accuracy: 0.8692
- F1: 0.8640
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: 16
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6463 | 0.77 | 50 | 0.5123 | 0.7936 | 0.7361 |
| 0.388 | 1.54 | 100 | 0.3818 | 0.8169 | 0.7658 |
| 0.2478 | 2.31 | 150 | 0.3972 | 0.8692 | 0.8640 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Feb 27, 2024
- Updated
- Feb 28, 2024