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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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