---
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-data-augumented-dra-tam-mal-aw-classification-finetune
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# m-minilm-l12-h384-data-augumented-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: 0.6411
- Accuracy: 0.7702
- F1: 0.8164

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6713        | 0.2222 | 20   | 0.6683          | 0.5998   | 0.7499 |
| 0.6494        | 0.4444 | 40   | 0.6559          | 0.6019   | 0.6459 |
| 0.6431        | 0.6667 | 60   | 0.6389          | 0.6508   | 0.7346 |
| 0.6079        | 0.8889 | 80   | 0.6318          | 0.6720   | 0.7166 |
| 0.5667        | 1.1111 | 100  | 0.5755          | 0.7021   | 0.7401 |
| 0.5353        | 1.3333 | 120  | 0.5437          | 0.7213   | 0.7927 |
| 0.5345        | 1.5556 | 140  | 0.5306          | 0.7482   | 0.7964 |
| 0.5178        | 1.7778 | 160  | 0.5366          | 0.7184   | 0.8031 |
| 0.4952        | 2.0    | 180  | 0.5046          | 0.7543   | 0.8050 |
| 0.4183        | 2.2222 | 200  | 0.5798          | 0.7278   | 0.7466 |
| 0.4257        | 2.4444 | 220  | 0.5373          | 0.7673   | 0.8075 |
| 0.3932        | 2.6667 | 240  | 0.5214          | 0.7665   | 0.8093 |
| 0.3914        | 2.8889 | 260  | 0.5125          | 0.7616   | 0.8133 |
| 0.3447        | 3.1111 | 280  | 0.5534          | 0.7653   | 0.8076 |
| 0.3122        | 3.3333 | 300  | 0.5874          | 0.7543   | 0.7901 |
| 0.3116        | 3.5556 | 320  | 0.5594          | 0.7649   | 0.8003 |
| 0.326         | 3.7778 | 340  | 0.5446          | 0.7661   | 0.8158 |
| 0.2979        | 4.0    | 360  | 0.5750          | 0.7681   | 0.8145 |
| 0.2457        | 4.2222 | 380  | 0.6121          | 0.7677   | 0.8140 |
| 0.2383        | 4.4444 | 400  | 0.5861          | 0.7689   | 0.8118 |
| 0.2396        | 4.6667 | 420  | 0.6161          | 0.7734   | 0.8156 |
| 0.2311        | 4.8889 | 440  | 0.5909          | 0.7751   | 0.8121 |
| 0.2139        | 5.1111 | 460  | 0.6411          | 0.7702   | 0.8164 |
| 0.2038        | 5.3333 | 480  | 0.6462          | 0.7718   | 0.8154 |
| 0.1884        | 5.5556 | 500  | 0.6443          | 0.7645   | 0.8043 |
| 0.1889        | 5.7778 | 520  | 0.6588          | 0.7665   | 0.8064 |
| 0.2081        | 6.0    | 540  | 0.6581          | 0.7665   | 0.8054 |


### Framework versions

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