wos_flat_1782296044
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4062
- Accuracy: 0.8069
- Precision Macro: 0.7929
- Recall Macro: 0.7801
- F1 Macro: 0.7828
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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 120
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 38
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro |
|---|---|---|---|---|---|---|---|
| 2.6446 | 1.0 | 2506 | 1.2083 | 0.7443 | 0.7249 | 0.6978 | 0.6884 |
| 0.9237 | 2.0 | 5012 | 0.9532 | 0.7873 | 0.7664 | 0.7543 | 0.7506 |
| 0.6276 | 3.0 | 7518 | 0.9017 | 0.8055 | 0.7912 | 0.7777 | 0.7792 |
| 0.4547 | 4.0 | 10024 | 0.9464 | 0.8049 | 0.7950 | 0.7814 | 0.7833 |
| 0.3283 | 5.0 | 12530 | 1.0243 | 0.8053 | 0.7946 | 0.7848 | 0.7861 |
| 0.2433 | 6.0 | 15036 | 1.1270 | 0.8058 | 0.7931 | 0.7814 | 0.7812 |
| 0.1726 | 7.0 | 17542 | 1.1630 | 0.8028 | 0.7955 | 0.7814 | 0.7845 |
| 0.1169 | 8.0 | 20048 | 1.3213 | 0.8036 | 0.7950 | 0.7779 | 0.7824 |
| 0.0813 | 9.0 | 22554 | 1.4062 | 0.8069 | 0.7929 | 0.7801 | 0.7828 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2