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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: edos-2023-baseline-xlm-roberta-base-label_vector
    results: []

edos-2023-baseline-xlm-roberta-base-label_vector

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5797
  • F1: 0.2746

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
2.1596 1.18 100 1.9772 0.0891
1.8651 2.35 200 1.7720 0.1159
1.6848 3.53 300 1.7193 0.1892
1.5532 4.71 400 1.6794 0.2191
1.466 5.88 500 1.6095 0.2419
1.3562 7.06 600 1.5771 0.2694
1.2909 8.24 700 1.5761 0.2707
1.2027 9.41 800 1.5747 0.2764
1.192 10.59 900 1.5893 0.2686
1.1256 11.76 1000 1.5797 0.2746

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2