---
library_name: transformers
license: mit
base_model: microsoft/Multilingual-MiniLM-L12-H384
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: m-minilm-l12-h384-dra-mal-ai-gen-review-classification-finetune
  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. -->

# m-minilm-l12-h384-dra-mal-ai-gen-review-classification-finetune

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4150
- Accuracy: 0.875
- F1: 0.8750

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6937        | 0.4   | 2    | 0.6906          | 0.5      | 0.3333 |
| 0.6895        | 0.8   | 4    | 0.6826          | 0.5      | 0.3333 |
| 0.6787        | 1.2   | 6    | 0.6546          | 0.9      | 0.8992 |
| 0.6425        | 1.6   | 8    | 0.5996          | 0.8875   | 0.8873 |
| 0.5733        | 2.0   | 10   | 0.5217          | 0.9062   | 0.9062 |
| 0.4975        | 2.4   | 12   | 0.4426          | 0.9375   | 0.9374 |
| 0.4349        | 2.8   | 14   | 0.4180          | 0.9125   | 0.9118 |
| 0.3776        | 3.2   | 16   | 0.3332          | 0.9688   | 0.9687 |
| 0.3462        | 3.6   | 18   | 0.3000          | 0.975    | 0.9750 |
| 0.303         | 4.0   | 20   | 0.2902          | 0.9563   | 0.9562 |
| 0.2832        | 4.4   | 22   | 0.2852          | 0.9563   | 0.9562 |
| 0.274         | 4.8   | 24   | 0.2749          | 0.9563   | 0.9562 |
| 0.2508        | 5.2   | 26   | 0.2688          | 0.9563   | 0.9562 |
| 0.2489        | 5.6   | 28   | 0.2640          | 0.9563   | 0.9562 |
| 0.246         | 6.0   | 30   | 0.2634          | 0.9563   | 0.9562 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0