metadata
library_name: transformers
base_model: ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: se_train_run_AUTOIMMUNE
results: []
se_train_run_AUTOIMMUNE
This model is a fine-tuned version of ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8454
- Model Preparation Time: 0.0023
- F1: 0.9142
- Precision: 0.8907
- Recall: 0.939
- Threshold: 0.6448
- Sim Ratio: 1.8668
- Pos Sim: 0.8175
- Neg Sim: 0.4379
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | F1 | Precision | Recall | Threshold | Sim Ratio | Pos Sim | Neg Sim |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.1666 | 0.1600 | 5000 | 3.8219 | 0.0023 | 0.8785 | 0.8627 | 0.8949 | 0.6512 | 1.8895 | 0.8276 | 0.438 |
| 1.0768 | 0.3201 | 10000 | 3.7588 | 0.0023 | 0.8937 | 0.8788 | 0.9092 | 0.6407 | 2.0951 | 0.8217 | 0.3922 |
| 0.9115 | 0.4801 | 15000 | 4.0146 | 0.0023 | 0.9012 | 0.872 | 0.9324 | 0.6185 | 2.1225 | 0.8194 | 0.386 |
| 0.8536 | 0.6402 | 20000 | 3.5470 | 0.0023 | 0.906 | 0.869 | 0.9464 | 0.6418 | 1.8244 | 0.8317 | 0.4559 |
| 0.8147 | 0.8002 | 25000 | 3.8247 | 0.0023 | 0.9115 | 0.8849 | 0.9398 | 0.6342 | 1.9331 | 0.8186 | 0.4235 |
| 0.799 | 0.9603 | 30000 | 3.8038 | 0.0023 | 0.914 | 0.8991 | 0.9295 | 0.6584 | 1.8577 | 0.8189 | 0.4408 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0