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---
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
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