metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model004
results: []
populism_model004
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: 0.4237
- Accuracy: 0.8668
- 1-f1: 0.3089
- 1-recall: 0.6296
- 1-precision: 0.2047
- Balanced Acc: 0.7541
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 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.4813 | 1.0 | 452 | 0.4548 | 0.8456 | 0.2689 | 0.6003 | 0.1732 | 0.7290 |
| 0.4154 | 2.0 | 904 | 0.4333 | 0.8261 | 0.2741 | 0.6940 | 0.1707 | 0.7634 |
| 0.3632 | 3.0 | 1356 | 0.4237 | 0.8668 | 0.3089 | 0.6296 | 0.2047 | 0.7541 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0