distilbert-base-cased-finetuned-ner-geocorpus
This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1175
- Precision: 0.8176
- Recall: 0.8651
- F1: 0.8407
- Accuracy: 0.9738
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 | 276 | 0.2104 | 0.6062 | 0.5413 | 0.5719 | 0.9489 |
0.2898 | 2.0 | 552 | 0.1456 | 0.7940 | 0.7310 | 0.7612 | 0.9648 |
0.2898 | 3.0 | 828 | 0.1225 | 0.7652 | 0.8021 | 0.7832 | 0.9671 |
0.1039 | 4.0 | 1104 | 0.1131 | 0.7590 | 0.8291 | 0.7925 | 0.9691 |
0.1039 | 5.0 | 1380 | 0.1086 | 0.8 | 0.8307 | 0.8151 | 0.9712 |
0.0585 | 6.0 | 1656 | 0.1188 | 0.7685 | 0.8741 | 0.8179 | 0.9689 |
0.0585 | 7.0 | 1932 | 0.1115 | 0.8009 | 0.8684 | 0.8333 | 0.9724 |
0.0349 | 8.0 | 2208 | 0.1196 | 0.8026 | 0.8708 | 0.8353 | 0.9728 |
0.0349 | 9.0 | 2484 | 0.1155 | 0.8317 | 0.8487 | 0.8401 | 0.9738 |
0.0235 | 10.0 | 2760 | 0.1175 | 0.8176 | 0.8651 | 0.8407 | 0.9738 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for GuiTap/distilbert-base-cased-finetuned-ner-geocorpus
Base model
distilbert/distilbert-base-cased