---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: upset-auk-708
  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. -->

# upset-auk-708

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: 0.3263
- Hamming Loss: 0.1113
- Zero One Loss: 0.9875
- Jaccard Score: 0.9869
- Hamming Loss Optimised: 0.1077
- Hamming Loss Threshold: 0.3523
- Zero One Loss Optimised: 0.785
- Zero One Loss Threshold: 0.2199
- Jaccard Score Optimised: 0.7435
- Jaccard Score Threshold: 0.2046

## 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: 1.090012056785563e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9422410857324217,0.913862773872536) 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  | 0.4186          | 0.1174       | 0.9862        | 0.9842        | 0.1123                 | 0.7028                 | 0.9275                  | 0.3569                  | 0.8325                  | 0.3103                  |
| No log        | 2.0   | 200  | 0.3414          | 0.1125       | 0.9988        | 0.9988        | 0.1123                 | 0.5944                 | 0.8362                  | 0.2346                  | 0.7740                  | 0.2016                  |
| No log        | 3.0   | 300  | 0.3295          | 0.1116       | 0.9912        | 0.9912        | 0.1091                 | 0.3329                 | 0.7875                  | 0.2167                  | 0.7499                  | 0.2120                  |
| No log        | 4.0   | 400  | 0.3263          | 0.1113       | 0.9875        | 0.9869        | 0.1077                 | 0.3523                 | 0.785                   | 0.2199                  | 0.7435                  | 0.2046                  |


### Framework versions

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