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germanic_antielite_Dutch

Text Classification
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bert
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End of training

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  1. README.md +11 -9
  2. model.safetensors +1 -1
  3. runs/Nov21_04-09-51_fb19369dd135/events.out.tfevents.1732162194.fb19369dd135.14490.1 +2 -2
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 [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4049
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- - Accuracy: 0.8660
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- - F1: 0.0
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  ## Model description
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@@ -46,15 +46,17 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
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- | No log | 1.0 | 97 | 0.3987 | 0.8660 | 0.0 |
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- | 0.3862 | 2.0 | 194 | 0.4112 | 0.8660 | 0.0 |
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- | 0.3746 | 3.0 | 291 | 0.4049 | 0.8660 | 0.0 |
 
 
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7833
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+ - Accuracy: 0.8299
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+ - F1: 0.0833
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  ## Model description
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 5
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 97 | 0.4203 | 0.8660 | 0.0 |
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+ | 0.3418 | 2.0 | 194 | 0.4251 | 0.8686 | 0.0377 |
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+ | 0.3252 | 3.0 | 291 | 0.5385 | 0.8634 | 0.0702 |
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+ | 0.2471 | 4.0 | 388 | 0.6629 | 0.8325 | 0.1096 |
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+ | 0.1156 | 5.0 | 485 | 0.7833 | 0.8299 | 0.0833 |
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  ### Framework versions
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