metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: bright-loon-253
results: []
bright-loon-253
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1606
- Hamming Loss: 0.0575
- Zero One Loss: 0.3938
- Jaccard Score: 0.3426
- Hamming Loss Optimised: 0.056
- Hamming Loss Threshold: 0.7152
- Zero One Loss Optimised: 0.3962
- Zero One Loss Threshold: 0.4832
- Jaccard Score Optimised: 0.3179
- Jaccard Score Threshold: 0.2879
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: 4.6017800734322744e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9392111443474531,0.8944286688071013) 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 | 0.1583 | 0.0599 | 0.4775 | 0.4292 | 0.0594 | 0.5609 | 0.4425 | 0.3912 | 0.3408 | 0.2948 |
| No log | 2.0 | 200 | 0.1515 | 0.0556 | 0.4075 | 0.3553 | 0.0566 | 0.7821 | 0.4 | 0.4285 | 0.3200 | 0.2934 |
| No log | 3.0 | 300 | 0.1606 | 0.0575 | 0.3938 | 0.3426 | 0.056 | 0.7152 | 0.3962 | 0.4832 | 0.3179 | 0.2879 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0