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---
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
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