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library_name: transformers
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
model-index:
- name: fold_4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fold_4
This model is a fine-tuned version of [UBC-NLP/MARBERT](https://huggingface.co/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
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