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metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: robeczech_lr3e-05_bs16_train287
    results: []

robeczech_lr3e-05_bs16_train287

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

  • Loss: 0.1179
  • Precision: 0.9454
  • Recall: 0.9595
  • F1: 0.9524
  • Accuracy: 0.9714

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.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: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 18 1.1550 1.0 0.0005 0.0010 0.5668
No log 2.0 36 0.4725 0.7099 0.7006 0.7052 0.8587
No log 3.0 54 0.2293 0.8740 0.8643 0.8691 0.9351
No log 4.0 72 0.1474 0.9224 0.9126 0.9175 0.9565
No log 5.0 90 0.1210 0.9457 0.9411 0.9434 0.9697
No log 6.0 108 0.1212 0.9409 0.9382 0.9396 0.9674
No log 7.0 126 0.1067 0.9540 0.9517 0.9529 0.9740
No log 8.0 144 0.0918 0.9574 0.9551 0.9562 0.9753
No log 9.0 162 0.1076 0.9549 0.9517 0.9533 0.9749
No log 10.0 180 0.0990 0.9599 0.9585 0.9592 0.9774
No log 11.0 198 0.1027 0.9673 0.9570 0.9621 0.9778

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.1