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--- |
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license: mit |
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base_model: pdelobelle/robbert-v2-dutch-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- recall |
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- accuracy |
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model-index: |
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- name: robbert_seed34_1311 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# robbert_seed34_1311 |
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3777 |
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- Precisions: 0.8501 |
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- Recall: 0.8262 |
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- F-measure: 0.8370 |
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- Accuracy: 0.9450 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 34 |
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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: 14 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| |
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| 0.4251 | 1.0 | 236 | 0.2557 | 0.7903 | 0.7339 | 0.7510 | 0.9248 | |
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| 0.2162 | 2.0 | 472 | 0.3018 | 0.8386 | 0.7336 | 0.7532 | 0.9200 | |
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| 0.1275 | 3.0 | 708 | 0.2461 | 0.8347 | 0.7758 | 0.7858 | 0.9364 | |
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| 0.0797 | 4.0 | 944 | 0.2773 | 0.8694 | 0.7843 | 0.8114 | 0.9383 | |
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| 0.049 | 5.0 | 1180 | 0.2767 | 0.8314 | 0.8143 | 0.8200 | 0.9419 | |
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| 0.03 | 6.0 | 1416 | 0.3036 | 0.8126 | 0.8106 | 0.8104 | 0.9407 | |
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| 0.0189 | 7.0 | 1652 | 0.3637 | 0.8051 | 0.8146 | 0.8073 | 0.9395 | |
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| 0.014 | 8.0 | 1888 | 0.3762 | 0.8479 | 0.7926 | 0.8135 | 0.9436 | |
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| 0.012 | 9.0 | 2124 | 0.3649 | 0.8486 | 0.8019 | 0.8205 | 0.9443 | |
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| 0.0045 | 10.0 | 2360 | 0.3966 | 0.8530 | 0.8000 | 0.8200 | 0.9431 | |
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| 0.0057 | 11.0 | 2596 | 0.3856 | 0.8564 | 0.8129 | 0.8307 | 0.9441 | |
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| 0.0054 | 12.0 | 2832 | 0.3777 | 0.8501 | 0.8262 | 0.8370 | 0.9450 | |
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| 0.0025 | 13.0 | 3068 | 0.3792 | 0.8608 | 0.8207 | 0.8369 | 0.9458 | |
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| 0.0019 | 14.0 | 3304 | 0.3859 | 0.8581 | 0.8149 | 0.8318 | 0.9455 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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