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my-model-MiniLM-Area

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lBober/my-model-MiniLM-Area

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  1. README.md +25 -25
  2. model.safetensors +1 -1
  3. runs/May26_10-41-43_04e338bea0e4/events.out.tfevents.1716720104.04e338bea0e4.15328.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -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: 1.3128
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- - Accuracy: 0.6043
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- - F1: 0.5286
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- - Precision: 0.4717
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- - Recall: 0.6043
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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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- | 1.8779 | 1.0 | 22 | 1.7587 | 0.3094 | 0.1462 | 0.0957 | 0.3094 |
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- | 1.7841 | 2.0 | 44 | 1.7061 | 0.3094 | 0.1462 | 0.0957 | 0.3094 |
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- | 1.7493 | 3.0 | 66 | 1.6460 | 0.4388 | 0.3251 | 0.2858 | 0.4388 |
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- | 1.6781 | 4.0 | 88 | 1.5695 | 0.4964 | 0.3684 | 0.2931 | 0.4964 |
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- | 1.6071 | 5.0 | 110 | 1.5254 | 0.4892 | 0.3664 | 0.3057 | 0.4892 |
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- | 1.5653 | 6.0 | 132 | 1.5095 | 0.4892 | 0.3682 | 0.3111 | 0.4892 |
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- | 1.4851 | 7.0 | 154 | 1.4530 | 0.5108 | 0.3828 | 0.3147 | 0.5108 |
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- | 1.4579 | 8.0 | 176 | 1.4585 | 0.4892 | 0.3655 | 0.3033 | 0.4892 |
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- | 1.4111 | 9.0 | 198 | 1.4121 | 0.5108 | 0.3828 | 0.3147 | 0.5108 |
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- | 1.3628 | 10.0 | 220 | 1.4197 | 0.4964 | 0.3986 | 0.3759 | 0.4964 |
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- | 1.3227 | 11.0 | 242 | 1.4058 | 0.5396 | 0.4495 | 0.3994 | 0.5396 |
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- | 1.28 | 12.0 | 264 | 1.3937 | 0.4964 | 0.3988 | 0.3810 | 0.4964 |
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- | 1.2424 | 13.0 | 286 | 1.3457 | 0.5324 | 0.4359 | 0.3996 | 0.5324 |
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- | 1.2156 | 14.0 | 308 | 1.3541 | 0.5683 | 0.4831 | 0.4213 | 0.5683 |
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- | 1.1711 | 15.0 | 330 | 1.3269 | 0.5899 | 0.5115 | 0.4739 | 0.5899 |
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- | 1.1453 | 16.0 | 352 | 1.3020 | 0.6043 | 0.5195 | 0.4593 | 0.6043 |
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- | 1.1201 | 17.0 | 374 | 1.3095 | 0.6115 | 0.5339 | 0.4784 | 0.6115 |
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- | 1.0841 | 18.0 | 396 | 1.3220 | 0.6043 | 0.5318 | 0.4789 | 0.6043 |
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- | 1.0784 | 19.0 | 418 | 1.3110 | 0.6115 | 0.5342 | 0.4763 | 0.6115 |
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- | 1.0642 | 20.0 | 440 | 1.3128 | 0.6043 | 0.5286 | 0.4717 | 0.6043 |
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  ### Framework versions
 
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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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  | 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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