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: robbert2809_lrate10
+  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. -->
+
+# robbert2809_lrate10
+
+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: 0.3760
+- Precision: 0.7615
+- Recall: 0.7517
+- F1: 0.7566
+- Accuracy: 0.8990
+
+## 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 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 118  | 0.4116          | 0.7166    | 0.7104 | 0.7135 | 0.8906   |
+| No log        | 2.0   | 236  | 0.3760          | 0.7615    | 0.7517 | 0.7566 | 0.8990   |
+| No log        | 3.0   | 354  | 0.4114          | 0.7428    | 0.7692 | 0.7558 | 0.9019   |
+| No log        | 4.0   | 472  | 0.4230          | 0.7881    | 0.7844 | 0.7862 | 0.9131   |
+| 0.1527        | 5.0   | 590  | 0.4550          | 0.7858    | 0.7716 | 0.7786 | 0.9092   |
+| 0.1527        | 6.0   | 708  | 0.4553          | 0.7876    | 0.8019 | 0.7947 | 0.9188   |
+| 0.1527        | 7.0   | 826  | 0.4824          | 0.7864    | 0.8001 | 0.7932 | 0.9181   |
+| 0.1527        | 8.0   | 944  | 0.4973          | 0.7922    | 0.7978 | 0.7950 | 0.9196   |
+
+
+### 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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