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fine_tuned_mBERT

Text Classification
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morten-j/fine_tuned_mBERT

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  1. README.md +15 -15
  2. model.safetensors +1 -1
  3. runs/Apr02_11-57-23_yoga/events.out.tfevents.1712051844.yoga.27180.0 +3 -0
  4. runs/Apr02_12-13-14_yoga/events.out.tfevents.1712052795.yoga.28568.0 +3 -0
  5. runs/Apr02_12-13-14_yoga/events.out.tfevents.1712052924.yoga.28568.1 +3 -0
  6. runs/Apr02_12-21-50_yoga/events.out.tfevents.1712053310.yoga.28898.0 +3 -0
  7. runs/Apr02_12-21-50_yoga/events.out.tfevents.1712053441.yoga.28898.1 +3 -0
  8. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1446
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- - F1: 0.6190
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- - F5: 0.6548
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- - Precision: 0.5417
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- - Recall: 0.7222
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  ## Model description
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@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 65 | 0.3086 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 130 | 0.2538 | 0.5352 | 0.6034 | 0.4130 | 0.76 |
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- | No log | 3.0 | 195 | 0.3520 | 0.3333 | 0.3107 | 0.4118 | 0.28 |
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- | No log | 4.0 | 260 | 0.1806 | 0.6531 | 0.6480 | 0.6667 | 0.64 |
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- | No log | 5.0 | 325 | 0.3014 | 0.5263 | 0.4697 | 0.7692 | 0.4 |
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- | No log | 6.0 | 390 | 0.2432 | 0.6667 | 0.6562 | 0.6957 | 0.64 |
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- | No log | 7.0 | 455 | 0.2808 | 0.7059 | 0.7112 | 0.6923 | 0.72 |
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- | 0.1489 | 8.0 | 520 | 0.2133 | 0.76 | 0.76 | 0.76 | 0.76 |
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- | 0.1489 | 9.0 | 585 | 0.2639 | 0.7692 | 0.7807 | 0.7407 | 0.8 |
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- | 0.1489 | 10.0 | 650 | 0.3313 | 0.6809 | 0.6646 | 0.7273 | 0.64 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2019
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+ - F1: 0.6471
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+ - F5: 0.6062
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+ - Precision: 0.7857
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+ - Recall: 0.55
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 65 | 0.2513 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 130 | 0.1252 | 0.7143 | 0.7555 | 0.625 | 0.8333 |
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+ | No log | 3.0 | 195 | 0.4816 | 0.3736 | 0.4858 | 0.2329 | 0.9444 |
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+ | No log | 4.0 | 260 | 0.1049 | 0.7333 | 0.6813 | 0.9167 | 0.6111 |
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+ | No log | 5.0 | 325 | 0.1410 | 0.75 | 0.7798 | 0.6818 | 0.8333 |
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+ | No log | 6.0 | 390 | 0.0593 | 0.9189 | 0.9285 | 0.8947 | 0.9444 |
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+ | No log | 7.0 | 455 | 0.0733 | 0.8649 | 0.8739 | 0.8421 | 0.8889 |
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+ | 0.135 | 8.0 | 520 | 0.0959 | 0.8718 | 0.8982 | 0.8095 | 0.9444 |
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+ | 0.135 | 9.0 | 585 | 0.0761 | 0.9189 | 0.9285 | 0.8947 | 0.9444 |
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+ | 0.135 | 10.0 | 650 | 0.0763 | 0.9189 | 0.9285 | 0.8947 | 0.9444 |
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  ### Framework versions
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