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_lrate10b32
+  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_lrate10b32
+
+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: 0.4435
+- Precisions: 0.8143
+- Recall: 0.8300
+- F-measure: 0.8201
+- Accuracy: 0.9162
+
+## 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: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.6187        | 1.0   | 118  | 0.3807          | 0.8761     | 0.6803 | 0.6943    | 0.8771   |
+| 0.3045        | 2.0   | 236  | 0.3297          | 0.7915     | 0.7331 | 0.7475    | 0.8966   |
+| 0.1748        | 3.0   | 354  | 0.3503          | 0.7831     | 0.7466 | 0.7553    | 0.9005   |
+| 0.1059        | 4.0   | 472  | 0.3670          | 0.8133     | 0.7784 | 0.7893    | 0.9086   |
+| 0.0649        | 5.0   | 590  | 0.3926          | 0.7875     | 0.7973 | 0.7908    | 0.9053   |
+| 0.0376        | 6.0   | 708  | 0.4213          | 0.7906     | 0.7922 | 0.7906    | 0.9082   |
+| 0.0221        | 7.0   | 826  | 0.4435          | 0.8143     | 0.8300 | 0.8201    | 0.9162   |
+| 0.014         | 8.0   | 944  | 0.4521          | 0.8170     | 0.8047 | 0.8090    | 0.9142   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0

pytorch_model.bin

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