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_model101
results: []
populism_model101
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: 0.1020
- Accuracy: 0.9736
- F1: 0.7660
- Recall: 0.9474
- Precision: 0.6429
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 | 13 | 0.2792 | 0.9639 | 0.5946 | 0.5789 | 0.6111 |
| No log | 2.0 | 26 | 0.1608 | 0.9736 | 0.7556 | 0.8947 | 0.6538 |
| No log | 3.0 | 39 | 0.1047 | 0.9736 | 0.7755 | 1.0 | 0.6333 |
| 0.258 | 4.0 | 52 | 0.1319 | 0.9712 | 0.7143 | 0.7895 | 0.6522 |
| 0.258 | 5.0 | 65 | 0.1020 | 0.9736 | 0.7660 | 0.9474 | 0.6429 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0