Downloads · 30 days
8
3% of all-time downloads
RuleBert-v0.5-k3
ribesstefano/RuleBert-v0.5-k3
RuleBert-v0.5-k3 is a text classification model from ribesstefano. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
275
Public
Parameters
278M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.1 GB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 7, 2024
- Updated
- Jan 7, 2024
- SHA
- 421c96b4
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. -->
ribesstefano/RuleBert-v0.5-k3
This model is a fine-tuned version of papluca/xlm-roberta-base-language-detection on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3277
- F1: 0.4513
- Roc Auc: 0.6511
- Accuracy: 0.0571
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-06
- train_batch_size: 2
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4223 | 0.06 | 250 | 0.3813 | 0.4517 | 0.6511 | 0.0571 |
| 0.3584 | 0.12 | 500 | 0.3377 | 0.4512 | 0.6506 | 0.0714 |
| 0.3591 | 0.18 | 750 | 0.3307 | 0.4507 | 0.6503 | 0.0714 |
| 0.3441 | 0.24 | 1000 | 0.3273 | 0.4515 | 0.6507 | 0.0714 |
| 0.3175 | 0.3 | 1250 | 0.3271 | 0.4507 | 0.6503 | 0.0714 |
| 0.3366 | 0.36 | 1500 | 0.3277 | 0.4513 | 0.6511 | 0.0571 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 7, 2024
- Updated
- Jan 7, 2024