metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ModernBERT-base-finetuned-modernbert
results: []
ModernBERT-base-finetuned-modernbert
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6023
- Accuracy: 0.9247
- F1: 0.9247
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|---|
| 1.4032 | 1.0 | 313 | 0.2615 | 0.9083 | 0.9081 |
| 0.6196 | 2.0 | 626 | 0.2596 | 0.9204 | 0.9203 |
| 0.2736 | 3.0 | 939 | 0.5185 | 0.9183 | 0.9181 |
| 0.0554 | 4.0 | 1252 | 0.5430 | 0.9263 | 0.9261 |
| 0.0052 | 5.0 | 1565 | 0.6023 | 0.9247 | 0.9247 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1