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my-model-MiniLM-Area

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lBober/my-model-MiniLM-Area

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  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -1,8 +1,8 @@
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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- base_model: Microsoft/Multilingual-MiniLM-L12-H384
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  metrics:
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  - accuracy
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  - f1
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2516
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- - Accuracy: 0.5827
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- - F1: 0.5228
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- - Precision: 0.4905
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- - Recall: 0.5827
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  ## Model description
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@@ -55,26 +55,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.8735 | 1.0 | 22 | 1.7614 | 0.3094 | 0.1462 | 0.0957 | 0.3094 |
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- | 1.7665 | 2.0 | 44 | 1.6764 | 0.4604 | 0.3485 | 0.3194 | 0.4604 |
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- | 1.683 | 3.0 | 66 | 1.5724 | 0.4964 | 0.3684 | 0.2930 | 0.4964 |
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- | 1.6038 | 4.0 | 88 | 1.5156 | 0.5108 | 0.3787 | 0.3015 | 0.5108 |
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- | 1.5742 | 5.0 | 110 | 1.4933 | 0.4820 | 0.3582 | 0.2921 | 0.4820 |
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- | 1.5197 | 6.0 | 132 | 1.4276 | 0.5252 | 0.3909 | 0.3125 | 0.5252 |
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- | 1.4965 | 7.0 | 154 | 1.4168 | 0.5180 | 0.3845 | 0.3058 | 0.5180 |
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- | 1.4305 | 8.0 | 176 | 1.4016 | 0.5396 | 0.4551 | 0.3970 | 0.5396 |
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- | 1.3606 | 9.0 | 198 | 1.3748 | 0.5108 | 0.3920 | 0.3845 | 0.5108 |
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- | 1.3442 | 10.0 | 220 | 1.4114 | 0.5324 | 0.4359 | 0.3926 | 0.5324 |
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- | 1.2944 | 11.0 | 242 | 1.3576 | 0.5540 | 0.4688 | 0.4111 | 0.5540 |
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- | 1.2317 | 12.0 | 264 | 1.3163 | 0.5468 | 0.4652 | 0.4048 | 0.5468 |
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- | 1.1677 | 13.0 | 286 | 1.2899 | 0.5612 | 0.4866 | 0.4355 | 0.5612 |
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- | 1.1331 | 14.0 | 308 | 1.3172 | 0.5683 | 0.5073 | 0.5480 | 0.5683 |
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- | 1.0908 | 15.0 | 330 | 1.2806 | 0.5468 | 0.4730 | 0.4395 | 0.5468 |
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- | 1.0785 | 16.0 | 352 | 1.2631 | 0.5540 | 0.4743 | 0.4149 | 0.5540 |
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- | 1.031 | 17.0 | 374 | 1.2667 | 0.5827 | 0.5159 | 0.4693 | 0.5827 |
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- | 1.0057 | 18.0 | 396 | 1.2617 | 0.5827 | 0.5224 | 0.5055 | 0.5827 |
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- | 0.9926 | 19.0 | 418 | 1.2477 | 0.5827 | 0.5223 | 0.4897 | 0.5827 |
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- | 0.9799 | 20.0 | 440 | 1.2516 | 0.5827 | 0.5228 | 0.4905 | 0.5827 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: Microsoft/Multilingual-MiniLM-L12-H384
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  tags:
5
  - generated_from_trainer
 
6
  metrics:
7
  - accuracy
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  - f1
 
20
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5228
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+ - Accuracy: 0.4323
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+ - F1: 0.3979
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+ - Precision: 0.3932
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+ - Recall: 0.4323
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.8812 | 1.0 | 25 | 1.8038 | 0.2839 | 0.1709 | 0.2712 | 0.2839 |
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+ | 1.8043 | 2.0 | 50 | 1.7540 | 0.3742 | 0.2586 | 0.2046 | 0.3742 |
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+ | 1.7687 | 3.0 | 75 | 1.6908 | 0.3806 | 0.2557 | 0.1927 | 0.3806 |
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+ | 1.6959 | 4.0 | 100 | 1.6325 | 0.4 | 0.2695 | 0.2033 | 0.4 |
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+ | 1.6178 | 5.0 | 125 | 1.6401 | 0.4129 | 0.3338 | 0.2874 | 0.4129 |
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+ | 1.5189 | 6.0 | 150 | 1.5471 | 0.4581 | 0.3631 | 0.3030 | 0.4581 |
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+ | 1.4393 | 7.0 | 175 | 1.5966 | 0.4258 | 0.3761 | 0.3451 | 0.4258 |
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+ | 1.3757 | 8.0 | 200 | 1.5716 | 0.4452 | 0.3945 | 0.3556 | 0.4452 |
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+ | 1.3032 | 9.0 | 225 | 1.5691 | 0.4387 | 0.3646 | 0.3443 | 0.4387 |
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+ | 1.2434 | 10.0 | 250 | 1.5740 | 0.4452 | 0.4057 | 0.3798 | 0.4452 |
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+ | 1.1837 | 11.0 | 275 | 1.5108 | 0.4645 | 0.3854 | 0.3852 | 0.4645 |
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+ | 1.1231 | 12.0 | 300 | 1.5409 | 0.4516 | 0.3972 | 0.3561 | 0.4516 |
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+ | 1.0815 | 13.0 | 325 | 1.5111 | 0.4774 | 0.4116 | 0.3865 | 0.4774 |
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+ | 1.0555 | 14.0 | 350 | 1.5171 | 0.4645 | 0.4014 | 0.3674 | 0.4645 |
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+ | 0.9964 | 15.0 | 375 | 1.4971 | 0.4581 | 0.3877 | 0.3504 | 0.4581 |
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+ | 0.9627 | 16.0 | 400 | 1.5157 | 0.4516 | 0.4118 | 0.3882 | 0.4516 |
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+ | 0.9247 | 17.0 | 425 | 1.4996 | 0.4387 | 0.3882 | 0.3664 | 0.4387 |
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+ | 0.9286 | 18.0 | 450 | 1.4990 | 0.4452 | 0.4008 | 0.3856 | 0.4452 |
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+ | 0.892 | 19.0 | 475 | 1.5288 | 0.4323 | 0.4025 | 0.4031 | 0.4323 |
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+ | 0.8843 | 20.0 | 500 | 1.5228 | 0.4323 | 0.3979 | 0.3932 | 0.4323 |
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  ### Framework versions
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