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---
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
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