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_model104
results: []
populism_model104
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: 0.5649
- Accuracy: 0.8550
- F1: 0.4368
- Recall: 0.7037
- Precision: 0.3167
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 | 0.4438 | 0.7870 | 0.3571 | 0.7407 | 0.2353 |
| No log | 2.0 | 22 | 0.4281 | 0.7456 | 0.3485 | 0.8519 | 0.2190 |
| No log | 3.0 | 33 | 0.4457 | 0.8284 | 0.42 | 0.7778 | 0.2877 |
| No log | 4.0 | 44 | 0.5020 | 0.8373 | 0.4211 | 0.7407 | 0.2941 |
| 0.3644 | 5.0 | 55 | 0.5649 | 0.8550 | 0.4368 | 0.7037 | 0.3167 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0