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Halaluka/bert-finetuned-ner
bert-finetuned-ner is a token classification model from Halaluka. 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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.safetensors431 MB · 100%
From the Hugging Face model README
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0905 | 1.0 | 878 | 0.0637 | 0.9022 | 0.9345 | 0.9181 | 0.9816 |
| 0.038 | 2.0 | 1756 | 0.0612 | 0.9228 | 0.9438 | 0.9332 | 0.9853 |
| 0.0213 | 3.0 | 2634 | 0.0574 | 0.9261 | 0.9465 | 0.9362 | 0.9861 |