---
library_name: peft
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: intelligent-vole-860
  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. -->

# intelligent-vole-860

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: 0.4774
- Hamming Loss: 0.1452
- Zero One Loss: 0.9275
- Jaccard Score: 0.9058
- Hamming Loss Optimised: 0.1123
- Hamming Loss Threshold: 0.7112
- Zero One Loss Optimised: 0.905
- Zero One Loss Threshold: 0.4615
- Jaccard Score Optimised: 0.8303
- Jaccard Score Threshold: 0.4021

## 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: 1.4188771076578358e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9321315533118193,0.8355607204472777) 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  | 0.5336          | 0.1984       | 0.9287        | 0.8619        | 0.1123                 | 0.7649                 | 0.9175                  | 0.5176                  | 0.8429                  | 0.4502                  |
| No log        | 2.0   | 200  | 0.4774          | 0.1452       | 0.9275        | 0.9058        | 0.1123                 | 0.7112                 | 0.905                   | 0.4615                  | 0.8303                  | 0.4021                  |


### Framework versions

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