| | --- |
| | library_name: transformers |
| | base_model: tbs17/MathBERT |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: tbs17-MathBERT-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. --> |
| |
|
| | # tbs17-MathBERT-Math-Classifier |
| |
|
| | This model is a fine-tuned version of [tbs17/MathBERT](https://huggingface.co/tbs17/MathBERT) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.9505 |
| | - Micro F1: 0.8437 |
| |
|
| | ## 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: 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=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 8 |
| | - mixed_precision_training: Native AMP |
| | - label_smoothing_factor: 0.1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Micro F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.2886 | 1.0 | 1083 | 0.8944 | 0.8051 | |
| | | 0.8314 | 2.0 | 2166 | 0.8812 | 0.8182 | |
| | | 0.6888 | 3.0 | 3249 | 0.8701 | 0.8411 | |
| | | 0.598 | 4.0 | 4332 | 0.9151 | 0.8352 | |
| | | 0.5407 | 5.0 | 5415 | 0.9424 | 0.8339 | |
| | | 0.5081 | 6.0 | 6498 | 0.9387 | 0.8457 | |
| | | 0.4908 | 7.0 | 7581 | 0.9565 | 0.8424 | |
| | | 0.4857 | 8.0 | 8664 | 0.9505 | 0.8437 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.51.1 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.21.0 |
| |
|
