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bwahyuh
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digidaw

Text Classification
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Safetensors
bert
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Training complete

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  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. runs/Jun10_05-06-38_1aea47f1a6c7/events.out.tfevents.1717996000.1aea47f1a6c7.500.0 +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 [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7597
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- - Accuracy: 0.7770
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- - Precision: 0.5252
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- - Recall: 0.5221
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- - F1: 0.5217
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  ## Model description
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@@ -55,9 +55,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 1.0326 | 1.0 | 110 | 0.7906 | 0.7557 | 0.5710 | 0.4468 | 0.4696 |
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- | 0.6609 | 2.0 | 220 | 0.7697 | 0.7597 | 0.5234 | 0.4885 | 0.4999 |
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- | 0.4276 | 3.0 | 330 | 0.7597 | 0.7770 | 0.5252 | 0.5221 | 0.5217 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.1093
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+ - Accuracy: 0.095
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+ - Precision: 0.0784
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+ - Recall: 0.1217
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+ - F1: 0.0557
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.9895 | 1.0 | 156 | 4.4196 | 0.089 | 0.0792 | 0.1167 | 0.0479 |
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+ | 0.6357 | 2.0 | 312 | 4.8610 | 0.089 | 0.0952 | 0.1160 | 0.0495 |
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+ | 0.3968 | 3.0 | 468 | 5.1093 | 0.095 | 0.0784 | 0.1217 | 0.0557 |
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  ### Framework versions
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