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End of training

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README.md ADDED
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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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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: robbertfinetuned2408
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+ results: []
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+ ---
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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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+
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+ # robbertfinetuned2408
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+
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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: 0.3389
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+ - Precision: 0.7133
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+ - Recall: 0.7552
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+ - F1: 0.7337
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+ - Accuracy: 0.8993
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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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: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 236 | 0.4185 | 0.6648 | 0.6218 | 0.6426 | 0.8720 |
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+ | No log | 2.0 | 472 | 0.3389 | 0.7133 | 0.7552 | 0.7337 | 0.8993 |
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+ | 0.4572 | 3.0 | 708 | 0.3503 | 0.7484 | 0.7646 | 0.7564 | 0.9046 |
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+ | 0.4572 | 4.0 | 944 | 0.3875 | 0.7607 | 0.7652 | 0.7629 | 0.9062 |
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+ | 0.1454 | 5.0 | 1180 | 0.4251 | 0.7854 | 0.7786 | 0.7820 | 0.9089 |
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+ | 0.1454 | 6.0 | 1416 | 0.4230 | 0.7878 | 0.7920 | 0.7899 | 0.9152 |
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+ | 0.0544 | 7.0 | 1652 | 0.4555 | 0.7983 | 0.7844 | 0.7913 | 0.9113 |
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+ | 0.0544 | 8.0 | 1888 | 0.4679 | 0.7894 | 0.7821 | 0.7857 | 0.9120 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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