metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: populism_model96
results: []
populism_model96
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3362
- Accuracy: 0.9513
- F1: 0.7302
- Recall: 0.8214
- Precision: 0.6571
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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 11 | 0.2642 | 0.8911 | 0.5778 | 0.9286 | 0.4194 |
| No log | 2.0 | 22 | 0.3199 | 0.9484 | 0.7188 | 0.8214 | 0.6389 |
| No log | 3.0 | 33 | 0.2950 | 0.9513 | 0.7463 | 0.8929 | 0.6410 |
| No log | 4.0 | 44 | 0.3220 | 0.9513 | 0.7302 | 0.8214 | 0.6571 |
| 0.1231 | 5.0 | 55 | 0.3362 | 0.9513 | 0.7302 | 0.8214 | 0.6571 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0