Downloads · 30 days
6
2% of all-time downloads
distilbert-base-uncased-finetuned-intro-verizon2
TieIncred/distilbert-base-uncased-finetuned-intro-verizon2
distilbert-base-uncased-finetuned-intro-verizon2 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
278
Public
Repo size
536 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
- a66e4705
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-verizon2
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: 0.0327
- 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 |
|---|---|---|---|---|---|
| 1.3459 | 1.0 | 7 | 1.2548 | 0.5814 | 0.4575 |
| 1.1898 | 2.0 | 14 | 1.0488 | 0.7209 | 0.6261 |
| 1.1052 | 3.0 | 21 | 0.7911 | 0.7442 | 0.6506 |
| 0.7628 | 4.0 | 28 | 0.5534 | 1.0 | 1.0 |
| 0.6325 | 5.0 | 35 | 0.3608 | 1.0 | 1.0 |
| 0.303 | 6.0 | 42 | 0.2387 | 1.0 | 1.0 |
| 0.2297 | 7.0 | 49 | 0.1626 | 1.0 | 1.0 |
| 0.1663 | 8.0 | 56 | 0.1152 | 1.0 | 1.0 |
| 0.1232 | 9.0 | 63 | 0.0866 | 1.0 | 1.0 |
| 0.1056 | 10.0 | 70 | 0.0683 | 1.0 | 1.0 |
| 0.0802 | 11.0 | 77 | 0.0572 | 1.0 | 1.0 |
| 0.0589 | 12.0 | 84 | 0.0497 | 1.0 | 1.0 |
| 0.0561 | 13.0 | 91 | 0.0445 | 1.0 | 1.0 |
| 0.0567 | 14.0 | 98 | 0.0404 | 1.0 | 1.0 |
| 0.0457 | 15.0 | 105 | 0.0376 | 1.0 | 1.0 |
| 0.0417 | 16.0 | 112 | 0.0357 | 1.0 | 1.0 |
| 0.0412 | 17.0 | 119 | 0.0344 | 1.0 | 1.0 |
| 0.0389 | 18.0 | 126 | 0.0335 | 1.0 | 1.0 |
| 0.04 | 19.0 | 133 | 0.0329 | 1.0 | 1.0 |
| 0.0394 | 20.0 | 140 | 0.0327 | 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