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livinNector
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m-minilm-l12-h384-booster-finetune

Text Classification
Transformers
Safetensors
bert
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End of training

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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -19,9 +19,9 @@ 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: 0.8722
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- - Accuracy: 0.4935
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- - F1: 0.6496
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  ## Model description
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@@ -52,12 +52,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.535 | 2.0 | 10 | 0.8722 | 0.4935 | 0.6496 |
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- | 0.3502 | 4.0 | 20 | 1.2356 | 0.4124 | 0.5339 |
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- | 0.2564 | 6.0 | 30 | 1.2356 | 0.4866 | 0.6418 |
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- | 0.2995 | 8.0 | 40 | 1.6847 | 0.3329 | 0.3792 |
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- | 0.1545 | 10.0 | 50 | 1.7194 | 0.3423 | 0.3987 |
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- | 0.1196 | 12.0 | 60 | 1.6383 | 0.3826 | 0.4877 |
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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: 0.6761
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+ - Accuracy: 0.5638
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+ - F1: 0.59
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6924 | 2.0 | 10 | 0.6725 | 0.6152 | 0.0091 |
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+ | 0.6671 | 4.0 | 20 | 0.6761 | 0.5638 | 0.59 |
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+ | 0.5174 | 6.0 | 30 | 0.6368 | 0.6543 | 0.5558 |
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+ | 0.2944 | 8.0 | 40 | 0.7570 | 0.6117 | 0.5748 |
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+ | 0.2225 | 10.0 | 50 | 0.7600 | 0.6507 | 0.5800 |
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+ | 0.2012 | 12.0 | 60 | 0.8511 | 0.6028 | 0.5805 |
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  ### Framework versions
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