Downloads · 30 days
7
4% of all-time downloads
distilbert-base-uncased
ui-chope/distilbert-base-uncased
distilbert-base-uncased is a token classification model from ui-chope. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
199
Public
Repo size
80.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin266 MB · 100%
At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jul 5, 2023
- Updated
- Jul 13, 2023
- SHA
- 183ca65b
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
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1298
- Precision: 0.9739
- Recall: 0.9617
- F1: 0.9678
- Accuracy: 0.9837
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0218 | 1.0 | 5296 | 0.0828 | 0.9609 | 0.9609 | 0.9609 | 0.9842 |
| 0.0159 | 2.0 | 10592 | 0.1135 | 0.9677 | 0.9602 | 0.9639 | 0.9820 |
| 0.0137 | 3.0 | 15888 | 0.0846 | 0.9631 | 0.9570 | 0.9600 | 0.9831 |
| 0.0074 | 4.0 | 21184 | 0.1179 | 0.9621 | 0.9523 | 0.9572 | 0.9804 |
| 0.0058 | 5.0 | 26480 | 0.1080 | 0.9763 | 0.9664 | 0.9713 | 0.9857 |
| 0.0056 | 6.0 | 31776 | 0.1273 | 0.9685 | 0.9594 | 0.9639 | 0.9828 |
| 0.0055 | 7.0 | 37072 | 0.1451 | 0.9637 | 0.9531 | 0.9584 | 0.9800 |
| 0.0035 | 8.0 | 42368 | 0.1345 | 0.9707 | 0.9563 | 0.9634 | 0.9805 |
| 0.0027 | 9.0 | 47664 | 0.1242 | 0.9739 | 0.9633 | 0.9686 | 0.9852 |
| 0.0018 | 10.0 | 52960 | 0.1232 | 0.9739 | 0.9633 | 0.9686 | 0.9844 |
| 0.0017 | 11.0 | 58256 | 0.1298 | 0.9739 | 0.9617 | 0.9678 | 0.9837 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.13.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- Created
- Jul 5, 2023
- Updated
- Jul 13, 2023