| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/deberta-v3-large |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: grammar-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. --> |
|
|
| # grammar-classifier |
|
|
| This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.0967 |
| - Exact Match: 0.0 |
| - Micro F1: 0.3075 |
| - Macro F1: 0.0334 |
| - Hamming Accuracy: 0.8806 |
| - Avg Pred Positives: 34.0 |
| - Avg Gold Positives: 13.5736 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - 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: cosine |
| - lr_scheduler_warmup_steps: 0.2 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Exact Match | Micro F1 | Macro F1 | Hamming Accuracy | Avg Pred Positives | Avg Gold Positives | |
| |:-------------:|:-----:|:----:|:---------------:|:-----------:|:--------:|:--------:|:----------------:|:------------------:|:------------------:| |
| | 0.2930 | 0.5 | 164 | 0.5663 | 0.0 | 0.3139 | 0.0288 | 0.9041 | 25.0 | 13.5736 | |
| | 0.1928 | 1.0 | 328 | 0.2720 | 0.0 | 0.4392 | 0.0256 | 0.9460 | 13.0 | 13.5736 | |
| | 0.0751 | 1.5 | 492 | 0.0559 | 0.0 | 0.5244 | 0.0234 | 0.9628 | 8.0 | 13.5736 | |
| | 33.3599 | 2.0 | 656 | 13.5265 | 0.0 | 0.2931 | 0.0226 | 0.9114 | 21.0 | 13.5736 | |
| | 19.0859 | 2.5 | 820 | 10.5864 | 0.0 | 0.2214 | 0.0302 | 0.8376 | 44.0 | 13.5736 | |
| | 8.6145 | 3.0 | 984 | 4.0967 | 0.0 | 0.3075 | 0.0334 | 0.8806 | 34.0 | 13.5736 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
| |
