Downloads · 30 days
3
1% of all-time downloads
distilbert-base-uncased-finetuned-pad-mult-clf-v2
netoferraz/distilbert-base-uncased-finetuned-pad-mult-clf-v2
distilbert-base-uncased-finetuned-pad-mult-clf-v2 is a text classification model from netoferraz. Use it when you need a label for a piece of text. 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. --
All-time downloads
255
Public
Parameters
67M
536 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jan 9, 2024
- Updated
- Feb 8, 2024
- SHA
- 44bd0fad
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. -->
distilbert-base-uncased-finetuned-pad-mult-clf-v2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5603
- Accuracy: 0.8182
- F1: 0.7530
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: 2e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 3 | 1.1843 | 0.5397 | 0.3783 |
| No log | 2.0 | 6 | 1.0491 | 0.5397 | 0.3783 |
| No log | 3.0 | 9 | 0.9692 | 0.5397 | 0.3783 |
| 1.1406 | 4.0 | 12 | 0.8981 | 0.5745 | 0.4501 |
| 1.1406 | 5.0 | 15 | 0.8277 | 0.7292 | 0.6618 |
| 1.1406 | 6.0 | 18 | 0.7654 | 0.7834 | 0.7178 |
| 0.862 | 7.0 | 21 | 0.7125 | 0.8046 | 0.7388 |
| 0.862 | 8.0 | 24 | 0.6680 | 0.8143 | 0.7480 |
| 0.862 | 9.0 | 27 | 0.6395 | 0.8162 | 0.7499 |
| 0.6971 | 10.0 | 30 | 0.6132 | 0.8162 | 0.7499 |
| 0.6971 | 11.0 | 33 | 0.5999 | 0.8182 | 0.7523 |
| 0.6971 | 12.0 | 36 | 0.5766 | 0.8221 | 0.7556 |
| 0.6971 | 13.0 | 39 | 0.5637 | 0.8221 | 0.7561 |
| 0.6012 | 14.0 | 42 | 0.5607 | 0.8182 | 0.7529 |
| 0.6012 | 15.0 | 45 | 0.5603 | 0.8182 | 0.7530 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 9, 2024
- Updated
- Feb 8, 2024