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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: robbert2809_lrate7.5
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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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+ # robbert2809_lrate7.5
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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: 0.3477
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+ - Precision: 0.7368
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+ - Recall: 0.7716
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+ - F1: 0.7538
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+ - Accuracy: 0.9017
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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: 7.5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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 | 118 | 0.3855 | 0.6721 | 0.6533 | 0.6625 | 0.8795 |
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+ | No log | 2.0 | 236 | 0.3511 | 0.6921 | 0.7284 | 0.7098 | 0.8880 |
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+ | No log | 3.0 | 354 | 0.3477 | 0.7368 | 0.7716 | 0.7538 | 0.9017 |
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+ | No log | 4.0 | 472 | 0.4055 | 0.7489 | 0.7628 | 0.7558 | 0.9019 |
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+ | 0.3159 | 5.0 | 590 | 0.3930 | 0.7506 | 0.7488 | 0.7497 | 0.9035 |
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+ | 0.3159 | 6.0 | 708 | 0.4131 | 0.7684 | 0.7716 | 0.7700 | 0.9082 |
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+ | 0.3159 | 7.0 | 826 | 0.4382 | 0.7714 | 0.7786 | 0.7749 | 0.9093 |
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+ | 0.3159 | 8.0 | 944 | 0.4478 | 0.7817 | 0.7698 | 0.7757 | 0.9097 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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