| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: modernBERT-Math-Classifier |
| 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. --> |
|
|
| # modernBERT-Math-Classifier |
|
|
| 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: 0.8325 |
| - Micro F1: 0.8502 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - total_train_batch_size: 8 |
| - total_eval_batch_size: 8 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| - label_smoothing_factor: 0.1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Micro F1 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 1.3184 | 1.0 | 1083 | 0.9248 | 0.7986 | |
| | 0.858 | 2.0 | 2166 | 0.8338 | 0.8424 | |
| | 0.6955 | 3.0 | 3249 | 0.8040 | 0.8561 | |
| | 0.5752 | 4.0 | 4332 | 0.8284 | 0.8463 | |
| | 0.5152 | 5.0 | 5415 | 0.8289 | 0.8502 | |
| | 0.4921 | 6.0 | 6498 | 0.8361 | 0.8424 | |
| | 0.4807 | 7.0 | 7581 | 0.8297 | 0.8502 | |
| | 0.4752 | 8.0 | 8664 | 0.8271 | 0.8561 | |
| | 0.4717 | 9.0 | 9747 | 0.8349 | 0.8476 | |
| | 0.4696 | 10.0 | 10830 | 0.8325 | 0.8502 | |
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| ### Framework versions |
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|
| - Transformers 4.51.1 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.0 |
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|
