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_model103
results: []
populism_model103
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: 0.4117
- Accuracy: 0.9346
- F1: 0.3902
- Recall: 0.5714
- Precision: 0.2963
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 | 12 | 0.3301 | 0.8377 | 0.2955 | 0.9286 | 0.1757 |
| No log | 2.0 | 24 | 0.2935 | 0.8717 | 0.3467 | 0.9286 | 0.2131 |
| No log | 3.0 | 36 | 0.3193 | 0.9110 | 0.3704 | 0.7143 | 0.25 |
| No log | 4.0 | 48 | 0.3602 | 0.9136 | 0.3265 | 0.5714 | 0.2286 |
| 0.318 | 5.0 | 60 | 0.4117 | 0.9346 | 0.3902 | 0.5714 | 0.2963 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0