MarBERT-finetuned-CrossVal-fnd
This model is a fine-tuned version of UBC-NLP/MARBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3192
- Macro F1: 0.8548
- Accuracy: 0.8604
- Precision: 0.8576
- Recall: 0.8526
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 123
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4936 | 1.0 | 1597 | 0.3589 | 0.8364 | 0.8431 | 0.8401 | 0.8337 |
| 0.3431 | 2.0 | 3194 | 0.3192 | 0.8548 | 0.8604 | 0.8576 | 0.8526 |
| 0.233 | 3.0 | 4791 | 0.3914 | 0.8502 | 0.8547 | 0.8495 | 0.8509 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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