metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: KoELECTRA-small-v3-modu-ner
results: []
KoELECTRA-small-v3-modu-ner
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1370
- Precision: 0.8146
- Recall: 0.8349
- F1: 0.8246
- Accuracy: 0.9609
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2272
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 3788 | 0.1367 | 0.8089 | 0.8240 | 0.8164 | 0.9595 |
| No log | 2.0 | 7576 | 0.1345 | 0.8130 | 0.8331 | 0.8229 | 0.9604 |
| 0.0953 | 3.0 | 11364 | 0.1370 | 0.8146 | 0.8349 | 0.8246 | 0.9609 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2