---
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-tam-mal-aw-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-tam-mal-aw-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: 0.5902
- Accuracy: 0.7441
- F1: 0.7577

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6813        | 0.4444 | 20   | 0.6168          | 0.6903   | 0.7027 |
| 0.6418        | 0.8889 | 40   | 0.5810          | 0.7058   | 0.7058 |
| 0.5704        | 1.3333 | 60   | 0.5545          | 0.7205   | 0.6946 |
| 0.5575        | 1.7778 | 80   | 0.5344          | 0.7359   | 0.7457 |
| 0.5107        | 2.2222 | 100  | 0.5341          | 0.7498   | 0.7256 |
| 0.4649        | 2.6667 | 120  | 0.5298          | 0.7506   | 0.7528 |
| 0.4559        | 3.1111 | 140  | 0.5420          | 0.7522   | 0.7185 |
| 0.4031        | 3.5556 | 160  | 0.5952          | 0.7253   | 0.7524 |
| 0.3834        | 4.0    | 180  | 0.5535          | 0.7596   | 0.7476 |
| 0.3359        | 4.4444 | 200  | 0.5902          | 0.7441   | 0.7577 |
| 0.3423        | 4.8889 | 220  | 0.5629          | 0.7563   | 0.7498 |
| 0.2728        | 5.3333 | 240  | 0.5906          | 0.7588   | 0.7513 |
| 0.289         | 5.7778 | 260  | 0.6064          | 0.7555   | 0.7496 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3