metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ModernBERT_large_Assign_4
results: []
ModernBERT_large_Assign_4
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1879
- Accuracy: 0.9668
- F1: 0.9664
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- 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: cosine
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9447 | 0.8386 | 400 | 0.2952 | 0.9387 | 0.9358 |
| 0.0999 | 1.6771 | 800 | 0.2098 | 0.9513 | 0.9506 |
| 0.0582 | 2.5157 | 1200 | 0.2062 | 0.9574 | 0.9570 |
| 0.0185 | 3.3543 | 1600 | 0.1982 | 0.9635 | 0.9629 |
| 0.011 | 4.1929 | 2000 | 0.2009 | 0.9639 | 0.9632 |
| 0.0044 | 5.0314 | 2400 | 0.1852 | 0.9671 | 0.9668 |
| 0.0022 | 5.8700 | 2800 | 0.1915 | 0.9665 | 0.9661 |
| 0.0009 | 6.7086 | 3200 | 0.1878 | 0.9665 | 0.9661 |
| 0.0002 | 7.5472 | 3600 | 0.1879 | 0.9668 | 0.9664 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1