---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: victorious-moose-736
  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. -->

# victorious-moose-736

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: 0.1689
- Hamming Loss: 0.0619
- Zero One Loss: 0.4450
- Jaccard Score: 0.3857
- Hamming Loss Optimised: 0.0592
- Hamming Loss Threshold: 0.7299
- Zero One Loss Optimised: 0.4387
- Zero One Loss Threshold: 0.4119
- Jaccard Score Optimised: 0.3464
- Jaccard Score Threshold: 0.2462

## 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: 2.115467719563917e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8101446041573426,0.9056914031952074) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4

### 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  | 0.1830          | 0.0644       | 0.5162        | 0.4740        | 0.0643                 | 0.4982                 | 0.4975                  | 0.3276                  | 0.3889                  | 0.2962                  |
| No log        | 2.0   | 200  | 0.1643          | 0.062        | 0.4625        | 0.3920        | 0.0597                 | 0.6455                 | 0.4587                  | 0.4816                  | 0.3518                  | 0.2755                  |
| No log        | 3.0   | 300  | 0.1678          | 0.0636       | 0.4550        | 0.3934        | 0.0595                 | 0.7017                 | 0.4425                  | 0.3683                  | 0.3441                  | 0.2888                  |
| No log        | 4.0   | 400  | 0.1689          | 0.0619       | 0.4450        | 0.3857        | 0.0592                 | 0.7299                 | 0.4387                  | 0.4119                  | 0.3464                  | 0.2462                  |


### Framework versions

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