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: robbert0510_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. -->
+
+# robbert0510_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: 0.5475
+- Precisions: 0.8362
+- Recall: 0.8085
+- F-measure: 0.8194
+- Accuracy: 0.9125
+
+## 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: 16
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.7157        | 1.0   | 236  | 0.4352          | 0.8401     | 0.6698 | 0.6760    | 0.8659   |
+| 0.3813        | 2.0   | 472  | 0.3616          | 0.8396     | 0.7184 | 0.7109    | 0.8865   |
+| 0.2577        | 3.0   | 708  | 0.3348          | 0.7982     | 0.7441 | 0.7329    | 0.8974   |
+| 0.1921        | 4.0   | 944  | 0.3984          | 0.7735     | 0.7155 | 0.7226    | 0.8923   |
+| 0.1359        | 5.0   | 1180 | 0.3888          | 0.8225     | 0.7811 | 0.7985    | 0.9052   |
+| 0.0971        | 6.0   | 1416 | 0.4391          | 0.8534     | 0.7724 | 0.7925    | 0.9073   |
+| 0.0723        | 7.0   | 1652 | 0.4377          | 0.8301     | 0.7890 | 0.8052    | 0.9087   |
+| 0.0523        | 8.0   | 1888 | 0.4648          | 0.8081     | 0.7923 | 0.7955    | 0.9090   |
+| 0.0417        | 9.0   | 2124 | 0.4922          | 0.7994     | 0.8128 | 0.8032    | 0.9109   |
+| 0.0352        | 10.0  | 2360 | 0.5001          | 0.8281     | 0.7925 | 0.8079    | 0.9128   |
+| 0.0295        | 11.0  | 2596 | 0.5171          | 0.8272     | 0.7938 | 0.8084    | 0.9110   |
+| 0.0217        | 12.0  | 2832 | 0.5475          | 0.8362     | 0.8085 | 0.8194    | 0.9125   |
+| 0.0157        | 13.0  | 3068 | 0.5540          | 0.8278     | 0.8071 | 0.8160    | 0.9130   |
+| 0.0196        | 14.0  | 3304 | 0.5659          | 0.8259     | 0.7924 | 0.8047    | 0.9116   |
+| 0.0134        | 15.0  | 3540 | 0.5725          | 0.8203     | 0.7877 | 0.8017    | 0.9113   |
+| 0.0106        | 16.0  | 3776 | 0.5762          | 0.8216     | 0.7842 | 0.7997    | 0.9109   |
+
+
+### 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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