metadata
library_name: transformers
base_model: ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: se_train_run_COPD
results: []
se_train_run_COPD
This model is a fine-tuned version of ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.8425
- Model Preparation Time: 0.0018
- F1: 0.8243
- Precision: 0.7807
- Recall: 0.8729
- Threshold: 0.7059
- Sim Ratio: 1.319
- Pos Sim: 0.821
- Neg Sim: 0.6224
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.6722 | 0.6039 | 5000 | 2.9257 | 0.0018 | 0.8139 | 0.7651 | 0.8692 | 0.6885 | 1.3473 | 0.8195 | 0.6082 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0