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eurobert-immigration-stance-negative

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metadata
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: EuroBERT-immigration-stance-positive
    results: []

EuroBERT-immigration-stance-positive

This model is a fine-tuned version of EuroBERT/EuroBERT-210m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1444
  • Accuracy: 0.7389
  • F1 Macro: 0.7210
  • Accuracy Balanced: 0.7165
  • F1 Micro: 0.7389
  • Precision Macro: 0.7342
  • Recall Macro: 0.7165
  • Precision Micro: 0.7389
  • Recall Micro: 0.7389

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: 4
  • eval_batch_size: 40
  • 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
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Macro Accuracy Balanced F1 Micro Precision Macro Recall Macro Precision Micro Recall Micro
0.697 1.0 654 0.6768 0.5908 0.3714 0.5 0.5908 0.2954 0.5 0.5908 0.5908
0.7267 2.0 1308 0.6543 0.5878 0.5797 0.6340 0.5878 0.6642 0.6340 0.5878 0.5878
0.7024 3.0 1962 0.9052 0.6779 0.6778 0.7044 0.6779 0.7076 0.7044 0.6779 0.6779
0.675 4.0 2616 1.1944 0.7206 0.7088 0.7073 0.7206 0.7108 0.7073 0.7206 0.7206
0.5142 5.0 3270 1.4177 0.7160 0.7097 0.7126 0.7160 0.7084 0.7126 0.7160 0.7160
0.3573 6.0 3924 1.6717 0.7267 0.7159 0.7148 0.7267 0.7172 0.7148 0.7267 0.7267
0.1643 7.0 4578 1.6307 0.7389 0.7295 0.7292 0.7389 0.7300 0.7292 0.7389 0.7389
0.1253 8.0 5232 1.8601 0.7374 0.7187 0.7141 0.7374 0.7331 0.7141 0.7374 0.7374
0.0937 9.0 5886 2.0865 0.7420 0.7209 0.7157 0.7420 0.7412 0.7157 0.7420 0.7420
0.0562 10.0 6540 2.1444 0.7389 0.7210 0.7165 0.7389 0.7342 0.7165 0.7389 0.7389

Framework versions

  • Transformers 4.50.0
  • Pytorch 2.6.0+cu124
  • Datasets 3.4.1
  • Tokenizers 0.21.1