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distilbert-base-uncased-finetuned-ner_1
clarissa-koh-chope/distilbert-base-uncased-finetuned-ner_1
distilbert-base-uncased-finetuned-ner_1 is a token classification model from clarissa-koh-chope. 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
- Oct 25, 2023
- Updated
- Oct 25, 2023
- SHA
- 9590a8d6
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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-ner_1
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0665
- Precision: 0.9774
- Recall: 0.9724
- F1: 0.9749
- Accuracy: 0.9909
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 |
|---|---|---|---|---|---|---|---|
| 0.0296 | 1.0 | 5237 | 0.0535 | 0.9554 | 0.9612 | 0.9583 | 0.9872 |
| 0.0152 | 2.0 | 10474 | 0.0507 | 0.9643 | 0.9643 | 0.9643 | 0.9880 |
| 0.0133 | 3.0 | 15711 | 0.0558 | 0.9622 | 0.9612 | 0.9617 | 0.9874 |
| 0.0081 | 4.0 | 20948 | 0.0709 | 0.9743 | 0.9663 | 0.9703 | 0.9890 |
| 0.008 | 5.0 | 26185 | 0.0401 | 0.9795 | 0.9755 | 0.9775 | 0.9919 |
| 0.0054 | 6.0 | 31422 | 0.0661 | 0.9764 | 0.9704 | 0.9734 | 0.9898 |
| 0.0013 | 7.0 | 36659 | 0.0492 | 0.9764 | 0.9724 | 0.9744 | 0.9921 |
| 0.0035 | 8.0 | 41896 | 0.0602 | 0.9755 | 0.9735 | 0.9745 | 0.9911 |
| 0.001 | 9.0 | 47133 | 0.0687 | 0.9774 | 0.9724 | 0.9749 | 0.9907 |
| 0.0015 | 10.0 | 52370 | 0.0663 | 0.9774 | 0.9724 | 0.9749 | 0.9909 |
| 0.0012 | 11.0 | 57607 | 0.0665 | 0.9774 | 0.9724 | 0.9749 | 0.9909 |
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
- License
- apache-2.0
- Created
- Oct 25, 2023
- Updated
- Oct 25, 2023