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: robbert_testrun
+  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. -->
+
+# robbert_testrun
+
+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: 0.5609
+- Precisions: 0.8558
+- Recall: 0.8234
+- F-measure: 0.8375
+- Accuracy: 0.9294
+
+## 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: 7.5e-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: 14
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.4449        | 1.0   | 285  | 0.3985          | 0.8120     | 0.6963 | 0.7240    | 0.8907   |
+| 0.19          | 2.0   | 570  | 0.3572          | 0.8522     | 0.7715 | 0.8031    | 0.9118   |
+| 0.0946        | 3.0   | 855  | 0.3966          | 0.8331     | 0.7816 | 0.8013    | 0.9168   |
+| 0.0492        | 4.0   | 1140 | 0.4321          | 0.8295     | 0.8127 | 0.8189    | 0.9187   |
+| 0.034         | 5.0   | 1425 | 0.4523          | 0.8123     | 0.8122 | 0.8097    | 0.9241   |
+| 0.0221        | 6.0   | 1710 | 0.5082          | 0.8111     | 0.8109 | 0.8097    | 0.9222   |
+| 0.015         | 7.0   | 1995 | 0.5375          | 0.8587     | 0.7934 | 0.8194    | 0.9212   |
+| 0.0121        | 8.0   | 2280 | 0.5233          | 0.8542     | 0.8256 | 0.8373    | 0.9292   |
+| 0.0077        | 9.0   | 2565 | 0.5259          | 0.8277     | 0.8235 | 0.8246    | 0.9286   |
+| 0.0063        | 10.0  | 2850 | 0.5609          | 0.8558     | 0.8234 | 0.8375    | 0.9294   |
+| 0.003         | 11.0  | 3135 | 0.5672          | 0.8176     | 0.8197 | 0.8169    | 0.9271   |
+| 0.002         | 12.0  | 3420 | 0.5968          | 0.8555     | 0.8184 | 0.8347    | 0.9294   |
+| 0.0021        | 13.0  | 3705 | 0.5846          | 0.8315     | 0.8222 | 0.8263    | 0.9269   |
+| 0.0016        | 14.0  | 3990 | 0.5905          | 0.8352     | 0.8167 | 0.8251    | 0.9263   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

pytorch_model.bin

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