---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: respected-auk-145
  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. -->

# respected-auk-145

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: 0.1608
- Hamming Loss: 0.059
- Zero One Loss: 0.4500
- Jaccard Score: 0.3949
- Hamming Loss Optimised: 0.058
- Hamming Loss Threshold: 0.5957
- Zero One Loss Optimised: 0.4275
- Zero One Loss Threshold: 0.3876
- Jaccard Score Optimised: 0.3382
- Jaccard Score Threshold: 0.3000

## 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: 2.981063961904907e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.913862773872536,0.981775961733248) 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  | 0.1681          | 0.065        | 0.4988        | 0.4526        | 0.0636                 | 0.5593                 | 0.47                    | 0.3764                  | 0.3616                  | 0.2689                  |
| No log        | 2.0   | 200  | 0.1608          | 0.059        | 0.4500        | 0.3949        | 0.058                  | 0.5957                 | 0.4275                  | 0.3876                  | 0.3382                  | 0.3000                  |


### Framework versions

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