---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: rare-mink-344
  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. -->

# rare-mink-344

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: 0.1684
- Hamming Loss: 0.0622
- Zero One Loss: 0.4775
- Jaccard Score: 0.4349
- Hamming Loss Optimised: 0.0619
- Hamming Loss Threshold: 0.5161
- Zero One Loss Optimised: 0.4525
- Zero One Loss Threshold: 0.3657
- Jaccard Score Optimised: 0.3635
- Jaccard Score Threshold: 0.2643

## 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: 1.8001716530301675e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8775527409811034,0.8351994879199208) 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  | 0.1861          | 0.0686       | 0.5262        | 0.4890        | 0.0679                 | 0.4904                 | 0.4975                  | 0.3930                  | 0.4236                  | 0.3044                  |
| No log        | 2.0   | 200  | 0.1684          | 0.0622       | 0.4775        | 0.4349        | 0.0619                 | 0.5161                 | 0.4525                  | 0.3657                  | 0.3635                  | 0.2643                  |


### Framework versions

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