End of training

README.md

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+---
+license: mit
+base_model: pdelobelle/robbert-v2-dutch-base
+tags:
+- generated_from_trainer
+metrics:
+- recall
+- accuracy
+model-index:
+- name: robbert0410_lrate7.5b16
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# robbert0410_lrate7.5b16
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.3288
+- Precisions: 0.8075
+- Recall: 0.7510
+- F-measure: 0.7624
+- Accuracy: 0.8998
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 7.5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| No log        | 1.0   | 236  | 0.3876          | 0.8471     | 0.6823 | 0.6916    | 0.8775   |
+| No log        | 2.0   | 472  | 0.3288          | 0.8075     | 0.7510 | 0.7624    | 0.8998   |
+| 0.4702        | 3.0   | 708  | 0.3771          | 0.7893     | 0.7610 | 0.7689    | 0.9031   |
+| 0.4702        | 4.0   | 944  | 0.4066          | 0.8057     | 0.7695 | 0.7808    | 0.9056   |
+| 0.1484        | 5.0   | 1180 | 0.4444          | 0.7936     | 0.7783 | 0.7846    | 0.9093   |
+| 0.1484        | 6.0   | 1416 | 0.4649          | 0.8234     | 0.8018 | 0.8092    | 0.9155   |
+| 0.0534        | 7.0   | 1652 | 0.4812          | 0.8001     | 0.7877 | 0.7932    | 0.9135   |
+| 0.0534        | 8.0   | 1888 | 0.4878          | 0.8097     | 0.7894 | 0.7978    | 0.9155   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0

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