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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 -16
  2. model.safetensors +1 -1
  3. runs/May25_20-31-24_54438e66731d/events.out.tfevents.1716669085.54438e66731d.23181.0 +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: 1.4852
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- - Accuracy: 0.4892
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- - F1: 0.3927
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- - Precision: 0.3289
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- - Recall: 0.4892
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  ## Model description
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@@ -49,22 +49,32 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.8469 | 1.0 | 81 | 1.7939 | 0.2446 | 0.0961 | 0.0598 | 0.2446 |
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- | 1.7515 | 2.0 | 162 | 1.7363 | 0.3453 | 0.2319 | 0.1909 | 0.3453 |
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- | 1.6348 | 3.0 | 243 | 1.6204 | 0.4029 | 0.2657 | 0.1988 | 0.4029 |
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- | 1.5572 | 4.0 | 324 | 1.6158 | 0.3741 | 0.2475 | 0.1873 | 0.3741 |
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- | 1.5085 | 5.0 | 405 | 1.5680 | 0.3885 | 0.2590 | 0.1972 | 0.3885 |
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- | 1.4737 | 6.0 | 486 | 1.5973 | 0.3813 | 0.2555 | 0.2021 | 0.3813 |
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- | 1.3872 | 7.0 | 567 | 1.5049 | 0.3957 | 0.2642 | 0.2033 | 0.3957 |
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- | 1.3258 | 8.0 | 648 | 1.4691 | 0.4892 | 0.3916 | 0.3266 | 0.4892 |
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- | 1.2954 | 9.0 | 729 | 1.4854 | 0.4820 | 0.3861 | 0.3225 | 0.4820 |
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- | 1.2626 | 10.0 | 810 | 1.4852 | 0.4892 | 0.3927 | 0.3289 | 0.4892 |
 
 
 
 
 
 
 
 
 
 
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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: 1.7030
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+ - Accuracy: 0.4604
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+ - F1: 0.4211
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+ - Precision: 0.4635
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+ - Recall: 0.4604
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.8269 | 1.0 | 81 | 1.7906 | 0.3022 | 0.1832 | 0.1444 | 0.3022 |
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+ | 1.6732 | 2.0 | 162 | 1.7044 | 0.3381 | 0.2021 | 0.1453 | 0.3381 |
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+ | 1.5682 | 3.0 | 243 | 1.6712 | 0.3381 | 0.2041 | 0.1462 | 0.3381 |
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+ | 1.474 | 4.0 | 324 | 1.6753 | 0.3165 | 0.1918 | 0.1435 | 0.3165 |
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+ | 1.3727 | 5.0 | 405 | 1.6871 | 0.3165 | 0.1913 | 0.1424 | 0.3165 |
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+ | 1.2838 | 6.0 | 486 | 1.7624 | 0.3094 | 0.1875 | 0.1450 | 0.3094 |
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+ | 1.2015 | 7.0 | 567 | 1.7454 | 0.3381 | 0.2555 | 0.2103 | 0.3381 |
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+ | 1.1481 | 8.0 | 648 | 1.6219 | 0.4173 | 0.3319 | 0.2848 | 0.4173 |
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+ | 1.0393 | 9.0 | 729 | 1.6179 | 0.4101 | 0.3515 | 0.4186 | 0.4101 |
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+ | 0.9609 | 10.0 | 810 | 1.5942 | 0.4460 | 0.4154 | 0.4790 | 0.4460 |
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+ | 0.8892 | 11.0 | 891 | 1.5765 | 0.4388 | 0.3927 | 0.3892 | 0.4388 |
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+ | 0.8146 | 12.0 | 972 | 1.5880 | 0.4532 | 0.4104 | 0.4634 | 0.4532 |
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+ | 0.7427 | 13.0 | 1053 | 1.6326 | 0.4604 | 0.4153 | 0.4649 | 0.4604 |
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+ | 0.6991 | 14.0 | 1134 | 1.8251 | 0.4317 | 0.3888 | 0.4749 | 0.4317 |
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+ | 0.641 | 15.0 | 1215 | 1.6103 | 0.4604 | 0.4210 | 0.4605 | 0.4604 |
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+ | 0.5892 | 16.0 | 1296 | 1.6240 | 0.4892 | 0.4462 | 0.4940 | 0.4892 |
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+ | 0.5565 | 17.0 | 1377 | 1.6828 | 0.4460 | 0.4002 | 0.4503 | 0.4460 |
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+ | 0.5202 | 18.0 | 1458 | 1.6728 | 0.4604 | 0.4204 | 0.4452 | 0.4604 |
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+ | 0.498 | 19.0 | 1539 | 1.6580 | 0.4964 | 0.4641 | 0.5068 | 0.4964 |
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+ | 0.48 | 20.0 | 1620 | 1.7030 | 0.4604 | 0.4211 | 0.4635 | 0.4604 |
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  ### Framework versions
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