metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-Questions-goodareas-classifier
results: []
ModernBERT-Questions-goodareas-classifier
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: 1.5872
- Accuracy: 0.7824
- Precision: 0.5864
- Recall: 0.5308
- F1: 0.5572
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: 7e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4442 | 1.0 | 461 | 0.4667 | 0.7457 | 0.5039 | 0.9147 | 0.6498 |
| 0.3773 | 2.0 | 922 | 0.6937 | 0.8081 | 0.6239 | 0.6445 | 0.6340 |
| 0.2833 | 3.0 | 1383 | 0.7664 | 0.8056 | 0.6161 | 0.6540 | 0.6345 |
| 0.1719 | 4.0 | 1844 | 1.0995 | 0.7836 | 0.5817 | 0.5735 | 0.5776 |
| 0.091 | 5.0 | 2305 | 1.5872 | 0.7824 | 0.5864 | 0.5308 | 0.5572 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0