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metadata
library_name: transformers
base_model: UBC-NLP/MARBERT
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: MARBERT_with_categories
    results: []

MARBERT_with_categories

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: 1.7872
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.4724

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use 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: 10

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 5 1.3124 0.0 0.0 0.0 0.625
No log 2.0 10 1.2426 0.0 0.0 0.0 0.625
No log 3.0 15 1.0762 0.0 0.0 0.0 0.625
No log 4.0 20 1.0386 0.0 0.0 0.0 0.6389
No log 5.0 25 0.9635 0.0 0.0 0.0 0.6528
No log 6.0 30 0.9486 0.0 0.0 0.0 0.6944
No log 7.0 35 0.9383 0.0 0.0 0.0 0.6944
No log 8.0 40 0.9533 0.0 0.0 0.0 0.6528
No log 9.0 45 0.9997 0.0 0.0 0.0 0.6528
No log 10.0 50 1.0130 0.0 0.0 0.0 0.6528

Framework versions

  • Transformers 4.48.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0