metadata
base_model: monologg/kobigbird-bert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: aha_classification
results: []
aha_classification
This model is a fine-tuned version of monologg/kobigbird-bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1156
- F1: 0.9617
- Roc Auc: 0.9682
- Accuracy: 0.9478
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 42 | 0.3257 | 0.8718 | 0.8998 | 0.8522 |
| No log | 2.0 | 84 | 0.1861 | 0.9451 | 0.9573 | 0.9217 |
| No log | 3.0 | 126 | 0.1474 | 0.9492 | 0.9595 | 0.9304 |
| No log | 4.0 | 168 | 0.1156 | 0.9617 | 0.9682 | 0.9478 |
| No log | 5.0 | 210 | 0.1185 | 0.9536 | 0.9637 | 0.9391 |
| No log | 6.0 | 252 | 0.1133 | 0.9492 | 0.9595 | 0.9304 |
| No log | 7.0 | 294 | 0.1098 | 0.9580 | 0.9679 | 0.9391 |
| No log | 8.0 | 336 | 0.1084 | 0.9536 | 0.9637 | 0.9391 |
| No log | 9.0 | 378 | 0.1167 | 0.9536 | 0.9637 | 0.9391 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1