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_model94
results: []
populism_model94
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: 0.5601
- Accuracy: 0.9043
- F1: 0.4368
- Recall: 0.5758
- Precision: 0.3519
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 | 16 | 0.3935 | 0.7773 | 0.3448 | 0.9091 | 0.2128 |
| No log | 2.0 | 32 | 0.4647 | 0.9023 | 0.4318 | 0.5758 | 0.3455 |
| No log | 3.0 | 48 | 0.4596 | 0.8926 | 0.4330 | 0.6364 | 0.3281 |
| 0.3278 | 4.0 | 64 | 0.4401 | 0.8887 | 0.4771 | 0.7879 | 0.3421 |
| 0.3278 | 5.0 | 80 | 0.5601 | 0.9043 | 0.4368 | 0.5758 | 0.3519 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0