---
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