---
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-ai-gen-review-classification-finetune-2b
  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-dra-tam-mal-ai-gen-review-classification-finetune-2b

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: 0.3138
- Accuracy: 0.91
- F1: 0.9096

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6887        | 0.3636 | 4    | 0.6661          | 0.9410   | 0.9409 |
| 0.6406        | 0.7273 | 8    | 0.5617          | 0.9410   | 0.9409 |
| 0.5088        | 1.0909 | 12   | 0.3921          | 0.9689   | 0.9689 |
| 0.3735        | 1.4545 | 16   | 0.2680          | 0.9689   | 0.9689 |
| 0.2684        | 1.8182 | 20   | 0.1984          | 0.9814   | 0.9814 |
| 0.2635        | 2.1818 | 24   | 0.1675          | 0.9814   | 0.9814 |
| 0.1909        | 2.5455 | 28   | 0.1471          | 0.9814   | 0.9814 |
| 0.2291        | 2.9091 | 32   | 0.1356          | 0.9814   | 0.9814 |
| 0.1167        | 3.2727 | 36   | 0.1371          | 0.9752   | 0.9751 |
| 0.151         | 3.6364 | 40   | 0.1414          | 0.9720   | 0.9720 |
| 0.1579        | 4.0    | 44   | 0.1152          | 0.9814   | 0.9814 |
| 0.1211        | 4.3636 | 48   | 0.1273          | 0.9752   | 0.9751 |
| 0.1427        | 4.7273 | 52   | 0.1273          | 0.9752   | 0.9751 |
| 0.1002        | 5.0909 | 56   | 0.1259          | 0.9752   | 0.9751 |
| 0.1076        | 5.4545 | 60   | 0.1251          | 0.9752   | 0.9751 |
| 0.099         | 5.8182 | 64   | 0.1302          | 0.9720   | 0.9720 |


### Framework versions

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