metadata
library_name: transformers
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
model-index:
- name: fold_4
results: []
fold_4
This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4025
- Macro F1: 0.8920
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: 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 |
|---|---|---|---|---|
| 0.9836 | 1.0 | 87 | 0.5345 | 0.7540 |
| 0.3982 | 2.0 | 174 | 0.3769 | 0.8723 |
| 0.2025 | 3.0 | 261 | 0.3329 | 0.8814 |
| 0.1355 | 4.0 | 348 | 0.3793 | 0.8971 |
| 0.0506 | 5.0 | 435 | 0.4025 | 0.8920 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2