---
library_name: transformers
base_model: gates04/Structured-NF4-KD-NID
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: Structured-NF4-KD-SD-NID
  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. -->

# Structured-NF4-KD-SD-NID

This model is a fine-tuned version of [gates04/Structured-NF4-KD-NID](https://huggingface.co/gates04/Structured-NF4-KD-NID) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0167
- Accuracy: 0.9922
- Precision: 0.9797
- Recall: 0.9349
- F1 score: 0.9446

## 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: 5e-05
- train_batch_size: 300
- eval_batch_size: 300
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.0297        | 1.0   | 3960  | 0.0223          | 0.9912   | 0.9325    | 0.9155 | 0.9185   |
| 0.0217        | 2.0   | 7920  | 0.0196          | 0.9917   | 0.9754    | 0.9261 | 0.9335   |
| 0.0166        | 3.0   | 11880 | 0.0186          | 0.9917   | 0.9786    | 0.9275 | 0.9354   |
| 0.0158        | 4.0   | 15840 | 0.0170          | 0.9921   | 0.9774    | 0.9354 | 0.9442   |
| 0.0129        | 5.0   | 19800 | 0.0167          | 0.9922   | 0.9797    | 0.9349 | 0.9446   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1