Downloads · 30 days
8
3% of all-time downloads
distilbert-base-uncased-finetuned-intro-verizon
TieIncred/distilbert-base-uncased-finetuned-intro-verizon
distilbert-base-uncased-finetuned-intro-verizon is a text classification model from TieIncred. 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
292
Public
Repo size
804 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024
- SHA
- 7726bbb1
Try a prompt
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-intro-verizon
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0400
- Accuracy: 1.0
- F1: 1.0
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: 64
- eval_batch_size: 64
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3753 | 1.0 | 3 | 0.2877 | 1.0 | 1.0 |
| 0.278 | 2.0 | 6 | 0.2253 | 1.0 | 1.0 |
| 0.2366 | 3.0 | 9 | 0.1788 | 1.0 | 1.0 |
| 0.1721 | 4.0 | 12 | 0.1433 | 1.0 | 1.0 |
| 0.1531 | 5.0 | 15 | 0.1173 | 1.0 | 1.0 |
| 0.117 | 6.0 | 18 | 0.0980 | 1.0 | 1.0 |
| 0.108 | 7.0 | 21 | 0.0841 | 1.0 | 1.0 |
| 0.0916 | 8.0 | 24 | 0.0737 | 1.0 | 1.0 |
| 0.0843 | 9.0 | 27 | 0.0656 | 1.0 | 1.0 |
| 0.0701 | 10.0 | 30 | 0.0594 | 1.0 | 1.0 |
| 0.0683 | 11.0 | 33 | 0.0546 | 1.0 | 1.0 |
| 0.0599 | 12.0 | 36 | 0.0508 | 1.0 | 1.0 |
| 0.058 | 13.0 | 39 | 0.0478 | 1.0 | 1.0 |
| 0.0512 | 14.0 | 42 | 0.0454 | 1.0 | 1.0 |
| 0.0523 | 15.0 | 45 | 0.0437 | 1.0 | 1.0 |
| 0.0515 | 16.0 | 48 | 0.0423 | 1.0 | 1.0 |
| 0.0468 | 17.0 | 51 | 0.0413 | 1.0 | 1.0 |
| 0.0472 | 18.0 | 54 | 0.0406 | 1.0 | 1.0 |
| 0.0479 | 19.0 | 57 | 0.0401 | 1.0 | 1.0 |
| 0.0474 | 20.0 | 60 | 0.0400 | 1.0 | 1.0 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024