m-minilm-l12-h384-dra-tam-mal-meso-meme-detection
This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6007
- Accuracy: 0.7117
- F1: 0.5328
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 |
---|---|---|---|---|---|
0.6781 | 0.1429 | 2 | 0.6605 | 0.6914 | 0.0 |
0.6443 | 0.2857 | 4 | 0.6301 | 0.6914 | 0.0 |
0.6228 | 0.4286 | 6 | 0.6174 | 0.6914 | 0.0 |
0.6402 | 0.5714 | 8 | 0.6174 | 0.6914 | 0.0 |
0.6163 | 0.7143 | 10 | 0.6154 | 0.6914 | 0.0 |
0.6341 | 0.8571 | 12 | 0.6053 | 0.6914 | 0.0 |
0.5962 | 1.0 | 14 | 0.5972 | 0.6914 | 0.0 |
0.5522 | 1.1429 | 16 | 0.5845 | 0.7027 | 0.0704 |
0.577 | 1.2857 | 18 | 0.5854 | 0.7050 | 0.4696 |
0.5719 | 1.4286 | 20 | 0.5862 | 0.7117 | 0.4711 |
0.5876 | 1.5714 | 22 | 0.6007 | 0.7005 | 0.4981 |
0.5926 | 1.7143 | 24 | 0.5921 | 0.7117 | 0.4286 |
0.5405 | 1.8571 | 26 | 0.6141 | 0.6937 | 0.4963 |
0.4942 | 2.0 | 28 | 0.6078 | 0.7050 | 0.4609 |
0.5655 | 2.1429 | 30 | 0.6009 | 0.7140 | 0.4253 |
0.5051 | 2.2857 | 32 | 0.6054 | 0.7005 | 0.4242 |
0.5001 | 2.4286 | 34 | 0.6251 | 0.6892 | 0.4889 |
0.577 | 2.5714 | 36 | 0.6136 | 0.6982 | 0.4766 |
0.5034 | 2.7143 | 38 | 0.5884 | 0.7252 | 0.4352 |
0.5306 | 2.8571 | 40 | 0.5927 | 0.7252 | 0.3370 |
0.5255 | 3.0 | 42 | 0.5869 | 0.7275 | 0.3920 |
0.4786 | 3.1429 | 44 | 0.6012 | 0.7095 | 0.4901 |
0.5422 | 3.2857 | 46 | 0.6149 | 0.6914 | 0.4982 |
0.5278 | 3.4286 | 48 | 0.5914 | 0.7117 | 0.4797 |
0.4985 | 3.5714 | 50 | 0.5752 | 0.7297 | 0.4340 |
0.5262 | 3.7143 | 52 | 0.5707 | 0.7365 | 0.4658 |
0.522 | 3.8571 | 54 | 0.5797 | 0.7027 | 0.45 |
0.528 | 4.0 | 56 | 0.5775 | 0.7095 | 0.4603 |
0.4883 | 4.1429 | 58 | 0.5714 | 0.7185 | 0.4589 |
0.4504 | 4.2857 | 60 | 0.5754 | 0.7275 | 0.4265 |
0.5175 | 4.4286 | 62 | 0.5786 | 0.7252 | 0.4135 |
0.4654 | 4.5714 | 64 | 0.5740 | 0.7252 | 0.4299 |
0.5111 | 4.7143 | 66 | 0.5812 | 0.7140 | 0.4641 |
0.4264 | 4.8571 | 68 | 0.5962 | 0.7095 | 0.5169 |
0.465 | 5.0 | 70 | 0.6007 | 0.7117 | 0.5328 |
0.464 | 5.1429 | 72 | 0.6002 | 0.7117 | 0.4961 |
0.3746 | 5.2857 | 74 | 0.5943 | 0.7207 | 0.4918 |
0.4431 | 5.4286 | 76 | 0.5853 | 0.7342 | 0.5 |
0.4365 | 5.5714 | 78 | 0.5741 | 0.7365 | 0.5021 |
0.4253 | 5.7143 | 80 | 0.5698 | 0.7387 | 0.5167 |
0.4767 | 5.8571 | 82 | 0.5682 | 0.7432 | 0.5328 |
0.4225 | 6.0 | 84 | 0.5676 | 0.7387 | 0.5285 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Base model
microsoft/Multilingual-MiniLM-L12-H384