---
library_name: peft
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: aged-bat-118
  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. -->

# aged-bat-118

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6719
- Hamming Loss: 0.4211
- Zero One Loss: 0.995
- Jaccard Score: 0.8984
- Hamming Loss Optimised: 0.1154
- Hamming Loss Threshold: 0.7245
- Zero One Loss Optimised: 0.97
- Zero One Loss Threshold: 0.5836
- Jaccard Score Optimised: 0.8868
- Jaccard Score Threshold: 0.2939

## 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: 6.873958576260693e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9097766016186105,0.8847932912441592) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| No log        | 1.0   | 100  | 0.6856          | 0.4451       | 0.9975        | 0.8990        | 0.113                  | 0.8060                 | 0.9738                  | 0.6291                  | 0.8871                  | 0.2985                  |
| No log        | 2.0   | 200  | 0.6719          | 0.4211       | 0.995         | 0.8984        | 0.1154                 | 0.7245                 | 0.97                    | 0.5836                  | 0.8868                  | 0.2939                  |


### Framework versions

- PEFT 0.13.2
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0