---
library_name: peft
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: popular-goose-411
  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. -->

# popular-goose-411

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: 0.6311
- Hamming Loss: 0.3421
- Zero One Loss: 0.9988
- Jaccard Score: 0.8636
- Hamming Loss Optimised: 0.1124
- Hamming Loss Threshold: 0.8318
- Zero One Loss Optimised: 0.9275
- Zero One Loss Threshold: 0.6512
- Jaccard Score Optimised: 0.8578
- Jaccard Score Threshold: 0.5254

## 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: 2.763618769712032e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9266629421127196,0.9390598859734118) 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  | 0.6402          | 0.3553       | 0.9988        | 0.8655        | 0.1123                 | 0.8748                 | 0.9300                  | 0.6583                  | 0.8587                  | 0.5286                  |
| No log        | 2.0   | 200  | 0.6311          | 0.3421       | 0.9988        | 0.8636        | 0.1124                 | 0.8318                 | 0.9275                  | 0.6512                  | 0.8578                  | 0.5254                  |


### Framework versions

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