metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modernbert_agree_classifier
results: []
modernbert_agree_classifier
This model is a fine-tuned version of answerdotai/ModernBERT-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5980
- Accuracy: 0.7721
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: 6.000000000000001e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- 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: constant
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8275 | 0.4286 | 50 | 0.5879 | 0.7721 |
| 1.6712 | 0.8571 | 100 | 0.5567 | 0.7653 |
| 2.2032 | 1.2829 | 150 | 0.6964 | 0.4626 |
| 1.4726 | 1.7114 | 200 | 0.4985 | 0.7891 |
| 1.9443 | 2.1371 | 250 | 0.7351 | 0.4048 |
| 2.2852 | 2.5657 | 300 | 0.5546 | 0.7721 |
| 0.9394 | 2.9943 | 350 | 0.5533 | 0.7653 |
| 4.5893 | 3.42 | 400 | 0.6459 | 0.7925 |
| 1.466 | 3.8486 | 450 | 0.5980 | 0.7721 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1