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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: robbert0410_lrate10b16
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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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+ # robbert0410_lrate10b16
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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: 0.4783
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+ - Precisions: 0.8324
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+ - Recall: 0.8123
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+ - F-measure: 0.8208
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+ - Accuracy: 0.9164
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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: 0.0001
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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 | Precisions | Recall | F-measure | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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+ | 0.6379 | 1.0 | 236 | 0.4156 | 0.8657 | 0.6790 | 0.6955 | 0.8798 |
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+ | 0.3257 | 2.0 | 472 | 0.3378 | 0.7529 | 0.7397 | 0.7336 | 0.8932 |
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+ | 0.1977 | 3.0 | 708 | 0.3737 | 0.7960 | 0.7383 | 0.7451 | 0.9003 |
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+ | 0.1197 | 4.0 | 944 | 0.4060 | 0.8446 | 0.7503 | 0.7696 | 0.9025 |
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+ | 0.0659 | 5.0 | 1180 | 0.4428 | 0.7851 | 0.7731 | 0.7779 | 0.9063 |
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+ | 0.0447 | 6.0 | 1416 | 0.4972 | 0.8285 | 0.7991 | 0.8124 | 0.9127 |
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+ | 0.0256 | 7.0 | 1652 | 0.4783 | 0.8324 | 0.8123 | 0.8208 | 0.9164 |
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+ | 0.0173 | 8.0 | 1888 | 0.4918 | 0.8251 | 0.8082 | 0.8159 | 0.9169 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.0