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bert-finetuned-ner
MPRaveau/bert-finetuned-ner
bert-finetuned-ner is a machine learning model from MPRaveau. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Aug 8, 2024
- Updated
- Aug 20, 2024
- SHA
- 6f534f43
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. -->
bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2440
- Precision: 0.4311
- Recall: 0.4246
- F1: 0.4278
- Accuracy: 0.8954
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 202 | 0.2465 | 0.4230 | 0.3745 | 0.3973 | 0.8945 |
| No log | 2.0 | 404 | 0.2350 | 0.4477 | 0.3967 | 0.4206 | 0.8990 |
| 0.2423 | 3.0 | 606 | 0.2440 | 0.4311 | 0.4246 | 0.4278 | 0.8954 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cpu
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- bert
- License
- apache-2.0
- Created
- Aug 8, 2024
- Updated
- Aug 20, 2024