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metadata
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-610m
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: nli-professional-status
    results: []

nli-professional-status

This model is a fine-tuned version of EuroBERT/EuroBERT-610m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5105
  • Accuracy: 0.8906
  • Precision Binary: 0.5169
  • Recall Binary: 0.3770
  • F1 Binary: 0.4360
  • Precision Micro: 0.8906
  • Recall Micro: 0.8906
  • F1 Micro: 0.8906
  • F1 Macro: 0.6877
  • Pr Auc: 0.8671
  • Cohen Kappa: 0.3771

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: 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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Binary Recall Binary F1 Binary Precision Micro Recall Micro F1 Micro F1 Macro Pr Auc Cohen Kappa
0.4706 1.0 544 0.3099 0.8925 0.5472 0.2377 0.3314 0.8925 0.8925 0.8925 0.6365 0.8528 0.2827
0.3256 2.0 1088 0.4521 0.8998 0.6275 0.2623 0.3699 0.8998 0.8998 0.8998 0.6578 0.8660 0.3253
0.2073 3.0 1632 0.5105 0.8906 0.5169 0.3770 0.4360 0.8906 0.8906 0.8906 0.6877 0.8671 0.3771

Framework versions

  • Transformers 4.52.2
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1