End of training

README.md

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+---
+license: mit
+base_model: pdelobelle/robbert-v2-dutch-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: robbertfinetuned2209
+  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. -->
+
+# robbertfinetuned2209
+
+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: 0.3479
+- Precision: 0.7445
+- Recall: 0.7657
+- F1: 0.7550
+- Accuracy: 0.9055
+
+## 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: 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 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 236  | 0.3944          | 0.6565    | 0.6282 | 0.6420 | 0.8781   |
+| No log        | 2.0   | 472  | 0.3546          | 0.6938    | 0.7354 | 0.7140 | 0.8901   |
+| 0.479         | 3.0   | 708  | 0.3479          | 0.7445    | 0.7657 | 0.7550 | 0.9055   |
+| 0.479         | 4.0   | 944  | 0.3944          | 0.7523    | 0.7733 | 0.7626 | 0.9049   |
+| 0.1591        | 5.0   | 1180 | 0.4177          | 0.7812    | 0.7657 | 0.7734 | 0.9082   |
+| 0.1591        | 6.0   | 1416 | 0.4467          | 0.7817    | 0.7931 | 0.7874 | 0.9121   |
+| 0.0594        | 7.0   | 1652 | 0.4706          | 0.7985    | 0.7873 | 0.7928 | 0.9125   |
+| 0.0594        | 8.0   | 1888 | 0.4751          | 0.7860    | 0.7960 | 0.7910 | 0.9140   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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