KUCI_Bert_Base_Finetuned
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2038
- F1: 0.5172
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: 1e-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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.1987 | 1.0 | 5196 | 1.1956 | 0.4711 |
| 1.1506 | 2.0 | 10392 | 1.1539 | 0.4989 |
| 1.0993 | 3.0 | 15588 | 1.1260 | 0.5131 |
| 1.0511 | 4.0 | 20784 | 1.1206 | 0.5172 |
| 1.0058 | 5.0 | 25980 | 1.1180 | 0.5269 |
| 0.9605 | 6.0 | 31176 | 1.1835 | 0.5264 |
| 0.9067 | 7.0 | 36372 | 1.1929 | 0.5235 |
| 0.8862 | 8.0 | 41568 | 1.2050 | 0.5198 |
| 0.8667 | 9.0 | 46764 | 1.2038 | 0.5172 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1