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: robbert0210_lrate2.5b16
+  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. -->
+
+# robbert0210_lrate2.5b16
+
+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: 0.3449
+- Precisions: 0.7846
+- Recall: 0.7358
+- F-measure: 0.7356
+- Accuracy: 0.8988
+
+## 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: 2.5e-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  | 0.4364          | 0.8256     | 0.6672 | 0.6709    | 0.8658   |
+| No log        | 2.0   | 472  | 0.3745          | 0.6875     | 0.7116 | 0.6970    | 0.8839   |
+| 0.5514        | 3.0   | 708  | 0.3449          | 0.7846     | 0.7358 | 0.7356    | 0.8988   |
+| 0.5514        | 4.0   | 944  | 0.3625          | 0.8042     | 0.7487 | 0.7552    | 0.9000   |
+| 0.2255        | 5.0   | 1180 | 0.3987          | 0.8037     | 0.7541 | 0.7618    | 0.9000   |
+| 0.2255        | 6.0   | 1416 | 0.4315          | 0.8049     | 0.7549 | 0.7636    | 0.9010   |
+| 0.1211        | 7.0   | 1652 | 0.4060          | 0.8170     | 0.7633 | 0.7785    | 0.9034   |
+| 0.1211        | 8.0   | 1888 | 0.4146          | 0.8162     | 0.7813 | 0.7927    | 0.9070   |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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