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my_ner_model
yadvi/my_ner_model
my_ner_model is a token classification model from yadvi. Use it when you need labels on individual words, such as names. 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. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Dec 6, 2023
- Updated
- Dec 7, 2023
- SHA
- fa9e82e7
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Base models
Datasets
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. -->
my_ner_model
This model is a fine-tuned version of distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3321
- Precision: 0.5759
- Recall: 0.4254
- F1: 0.4893
- Accuracy: 0.9489
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.2766 | 0.5657 | 0.2873 | 0.3811 | 0.9399 |
| No log | 2.0 | 426 | 0.2634 | 0.6267 | 0.3438 | 0.4440 | 0.9447 |
| 0.1828 | 3.0 | 639 | 0.3173 | 0.6354 | 0.2697 | 0.3787 | 0.9432 |
| 0.1828 | 4.0 | 852 | 0.3102 | 0.6018 | 0.3670 | 0.4560 | 0.9470 |
| 0.0475 | 5.0 | 1065 | 0.3047 | 0.5914 | 0.3957 | 0.4742 | 0.9478 |
| 0.0475 | 6.0 | 1278 | 0.3226 | 0.5927 | 0.4059 | 0.4818 | 0.9481 |
| 0.0475 | 7.0 | 1491 | 0.3109 | 0.5709 | 0.4291 | 0.4899 | 0.9486 |
| 0.0212 | 8.0 | 1704 | 0.3609 | 0.6200 | 0.3855 | 0.4754 | 0.9474 |
| 0.0212 | 9.0 | 1917 | 0.3236 | 0.5587 | 0.4365 | 0.4901 | 0.9486 |
| 0.0117 | 10.0 | 2130 | 0.3321 | 0.5759 | 0.4254 | 0.4893 | 0.9489 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 6, 2023
- Updated
- Dec 7, 2023