metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: category-classifier
results: []
category-classifier
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: 1.6405
- F1: 0.7106
- Accuracy: 0.7150
- F1 Ai: 0.6377
- F1 Programming: 0.6682
- F1 Science & engineering: 0.6115
- F1 Tech: 0.4547
- F1 Rejected: 0.8019
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 5
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | F1 Ai | F1 Programming | F1 Science & engineering | F1 Tech | F1 Rejected |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.591 | 1.0 | 849 | 0.7085 | 0.6909 | 0.7084 | 0.6614 | 0.6502 | 0.6271 | 0.2727 | 0.8018 |
| 0.3318 | 2.0 | 1698 | 0.7817 | 0.7086 | 0.7160 | 0.6337 | 0.6359 | 0.6104 | 0.45 | 0.8060 |
| 0.1606 | 3.0 | 2547 | 1.6405 | 0.7106 | 0.7150 | 0.6377 | 0.6682 | 0.6115 | 0.4547 | 0.8019 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.21.0