metadata
library_name: transformers
license: cc-by-4.0
base_model: NbAiLab/nb-bert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: nb-bert-edu-scorer
results: []
nb-bert-edu-scorer
This model is a fine-tuned version of NbAiLab/nb-bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7249
- Precision: 0.3908
- Recall: 0.3347
- F1 Macro: 0.3334
- Accuracy: 0.48
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: 256
- eval_batch_size: 128
- seed: 0
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 2.4712 | 0.0986 | 0.1654 | 0.0877 | 0.3496 |
| 0.7734 | 2.6882 | 1000 | 0.7629 | 0.3988 | 0.3258 | 0.3215 | 0.4652 |
| 0.7602 | 5.3763 | 2000 | 0.7505 | 0.3938 | 0.3319 | 0.3284 | 0.4584 |
| 0.7548 | 8.0645 | 3000 | 0.7345 | 0.3924 | 0.3345 | 0.3319 | 0.4758 |
| 0.731 | 10.7527 | 4000 | 0.7300 | 0.3951 | 0.3359 | 0.3335 | 0.4756 |
| 0.7481 | 13.4409 | 5000 | 0.7274 | 0.3957 | 0.3356 | 0.3337 | 0.4818 |
| 0.7255 | 16.1290 | 6000 | 0.7263 | 0.3910 | 0.3361 | 0.3339 | 0.4754 |
| 0.7371 | 18.8172 | 7000 | 0.7249 | 0.3908 | 0.3347 | 0.3334 | 0.48 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2