metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model113
results: []
populism_model113
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: 0.2841
- Accuracy: 0.9761
- 1-f1: 0.1224
- 1-recall: 0.1
- 1-precision: 0.1579
- Balanced Acc: 0.5455
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.4288 | 1.0 | 113 | 0.3969 | 0.9833 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.2353 | 2.0 | 226 | 0.2867 | 0.9705 | 0.1587 | 0.1667 | 0.1515 | 0.5754 |
| 0.2045 | 3.0 | 339 | 0.2841 | 0.9761 | 0.1224 | 0.1 | 0.1579 | 0.5455 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0