---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: honorable-shrew-498
  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. -->

# honorable-shrew-498

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: 0.1625
- Hamming Loss: 0.055
- Zero One Loss: 0.3725
- Jaccard Score: 0.3189
- Hamming Loss Optimised: 0.0541
- Hamming Loss Threshold: 0.7220
- Zero One Loss Optimised: 0.3712
- Zero One Loss Threshold: 0.4879
- Jaccard Score Optimised: 0.2997
- Jaccard Score Threshold: 0.2962

## 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: 8.935925952705373e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8778562665922138,0.8720892866629456) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### 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  | 0.1595          | 0.0571       | 0.4600        | 0.4159        | 0.0559                 | 0.4890                 | 0.4225                  | 0.3826                  | 0.3403                  | 0.2310                  |
| No log        | 2.0   | 200  | 0.1476          | 0.0564       | 0.3975        | 0.3373        | 0.0551                 | 0.5746                 | 0.3875                  | 0.4361                  | 0.2977                  | 0.2865                  |
| No log        | 3.0   | 300  | 0.1625          | 0.055        | 0.3725        | 0.3189        | 0.0541                 | 0.7220                 | 0.3712                  | 0.4879                  | 0.2997                  | 0.2962                  |


### Framework versions

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