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: 0.0276
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0
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 | 50 | 0.2740 | 0.9906 | 0.9930 | 0.9857 |
| No log | 2.0 | 100 | 0.1222 | 0.9938 | 0.9962 | 0.9857 |
| No log | 3.0 | 150 | 0.0663 | 0.9969 | 0.9981 | 0.9929 |
| No log | 4.0 | 200 | 0.0423 | 0.9969 | 0.9981 | 0.9929 |
| No log | 5.0 | 250 | 0.0276 | 1.0 | 1.0 | 1.0 |
| No log | 6.0 | 300 | 0.0208 | 1.0 | 1.0 | 1.0 |
| No log | 7.0 | 350 | 0.0165 | 1.0 | 1.0 | 1.0 |
| No log | 8.0 | 400 | 0.0135 | 1.0 | 1.0 | 1.0 |
| No log | 9.0 | 450 | 0.0114 | 1.0 | 1.0 | 1.0 |
| 0.1025 | 10.0 | 500 | 0.0101 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1