Downloads · 30 days
8
35% of all-time downloads
test-ner
hr-wesbeaver/test-ner
test-ner is a machine learning model from hr-wesbeaver. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
23
Public
Parameters
109M
1.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin436 MB · 50%
At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jun 19, 2024
- Updated
- Jun 19, 2024
- SHA
- 236e8e7f
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. -->
test-ner
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0699
- Precision: 0.3475
- Recall: 0.3068
- F1: 0.3259
- Accuracy: 0.9793
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0803 | 1.0 | 78 | 0.0882 | 0.1874 | 0.0759 | 0.1081 | 0.9749 |
| 0.0938 | 2.0 | 156 | 0.0699 | 0.3475 | 0.3068 | 0.3259 | 0.9793 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.15.2
- Library
- transformers
- License
- apache-2.0
- Created
- Jun 19, 2024
- Updated
- Jun 19, 2024