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electra-srb-ner
This model was trained from scratch on the wikiann dataset. It achieves the following results on the evaluation set:
- Loss: 0.3406
- Precision: 0.8934
- Recall: 0.9087
- F1: 0.9010
- Accuracy: 0.9568
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3686 | 1.0 | 625 | 0.2108 | 0.8326 | 0.8494 | 0.8409 | 0.9335 |
| 0.1886 | 2.0 | 1250 | 0.1784 | 0.8737 | 0.8713 | 0.8725 | 0.9456 |
| 0.1323 | 3.0 | 1875 | 0.1805 | 0.8654 | 0.8870 | 0.8760 | 0.9468 |
| 0.0675 | 4.0 | 2500 | 0.2018 | 0.8736 | 0.8880 | 0.8807 | 0.9502 |
| 0.0425 | 5.0 | 3125 | 0.2162 | 0.8818 | 0.8945 | 0.8881 | 0.9512 |
| 0.0343 | 6.0 | 3750 | 0.2492 | 0.8790 | 0.8928 | 0.8859 | 0.9513 |
| 0.0253 | 7.0 | 4375 | 0.2562 | 0.8821 | 0.9006 | 0.8912 | 0.9525 |
| 0.0142 | 8.0 | 5000 | 0.2788 | 0.8807 | 0.9013 | 0.8909 | 0.9524 |
| 0.0114 | 9.0 | 5625 | 0.2793 | 0.8861 | 0.9002 | 0.8931 | 0.9534 |
| 0.0095 | 10.0 | 6250 | 0.2967 | 0.8887 | 0.9034 | 0.8960 | 0.9550 |
| 0.008 | 11.0 | 6875 | 0.2993 | 0.8899 | 0.9067 | 0.8982 | 0.9556 |
| 0.0048 | 12.0 | 7500 | 0.3215 | 0.8887 | 0.9038 | 0.8962 | 0.9545 |
| 0.0034 | 13.0 | 8125 | 0.3242 | 0.8897 | 0.9068 | 0.8982 | 0.9554 |
| 0.003 | 14.0 | 8750 | 0.3311 | 0.8884 | 0.9085 | 0.8983 | 0.9559 |
| 0.0025 | 15.0 | 9375 | 0.3383 | 0.8943 | 0.9062 | 0.9002 | 0.9562 |
| 0.0011 | 16.0 | 10000 | 0.3346 | 0.8941 | 0.9112 | 0.9026 | 0.9574 |
| 0.0015 | 17.0 | 10625 | 0.3362 | 0.8944 | 0.9081 | 0.9012 | 0.9567 |
| 0.001 | 18.0 | 11250 | 0.3464 | 0.8877 | 0.9100 | 0.8987 | 0.9559 |
| 0.0012 | 19.0 | 11875 | 0.3415 | 0.8944 | 0.9089 | 0.9016 | 0.9568 |
| 0.0005 | 20.0 | 12500 | 0.3406 | 0.8934 | 0.9087 | 0.9010 | 0.9568 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0
- Datasets 1.11.0
- Tokenizers 0.10.1
