---
library_name: transformers
base_model: ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: se_train_run_COPD
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# se_train_run_COPD

This model is a fine-tuned version of [ModernBERT-base](https://huggingface.co/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