---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: dazzling-hound-586
  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. -->

# dazzling-hound-586

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: 0.2093
- Hamming Loss: 0.0755
- Zero One Loss: 0.6188
- Jaccard Score: 0.5985
- Hamming Loss Optimised: 0.075
- Hamming Loss Threshold: 0.4882
- Zero One Loss Optimised: 0.5513
- Zero One Loss Threshold: 0.2887
- Jaccard Score Optimised: 0.4541
- Jaccard Score Threshold: 0.2220

## 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: 5.871069949578436e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8955773174153844,0.9360886643830869) 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  | 0.2884          | 0.0989       | 0.8588        | 0.8569        | 0.0953                 | 0.3770                 | 0.7338                  | 0.2090                  | 0.6634                  | 0.1684                  |
| No log        | 2.0   | 200  | 0.2256          | 0.0801       | 0.6700        | 0.6558        | 0.0783                 | 0.4253                 | 0.5713                  | 0.2674                  | 0.4899                  | 0.2186                  |
| No log        | 3.0   | 300  | 0.2093          | 0.0755       | 0.6188        | 0.5985        | 0.075                  | 0.4882                 | 0.5513                  | 0.2887                  | 0.4541                  | 0.2220                  |


### Framework versions

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