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_lrate9b16
+  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_lrate9b16
+
+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: 0.5873
+- Precisions: 0.8240
+- Recall: 0.8030
+- F-measure: 0.8121
+- Accuracy: 0.9175
+
+## 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: 9e-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 |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.6115        | 1.0   | 236  | 0.3939          | 0.8592     | 0.6769 | 0.6912    | 0.8757   |
+| 0.3166        | 2.0   | 472  | 0.3750          | 0.7447     | 0.7640 | 0.7458    | 0.8897   |
+| 0.194         | 3.0   | 708  | 0.3445          | 0.7683     | 0.7462 | 0.7525    | 0.9025   |
+| 0.1292        | 4.0   | 944  | 0.3776          | 0.8345     | 0.7570 | 0.7754    | 0.9072   |
+| 0.0755        | 5.0   | 1180 | 0.4667          | 0.7897     | 0.8244 | 0.7995    | 0.9079   |
+| 0.0556        | 6.0   | 1416 | 0.4879          | 0.8233     | 0.7809 | 0.7973    | 0.9086   |
+| 0.0413        | 7.0   | 1652 | 0.4901          | 0.7770     | 0.8020 | 0.7846    | 0.9049   |
+| 0.0245        | 8.0   | 1888 | 0.5467          | 0.8159     | 0.7679 | 0.7836    | 0.9086   |
+| 0.015         | 9.0   | 2124 | 0.5914          | 0.8156     | 0.7858 | 0.7957    | 0.9109   |
+| 0.0129        | 10.0  | 2360 | 0.5640          | 0.8041     | 0.8160 | 0.8079    | 0.9133   |
+| 0.0055        | 11.0  | 2596 | 0.5848          | 0.8084     | 0.8044 | 0.8055    | 0.9142   |
+| 0.0068        | 12.0  | 2832 | 0.5752          | 0.8097     | 0.7957 | 0.8017    | 0.9140   |
+| 0.0036        | 13.0  | 3068 | 0.5873          | 0.8240     | 0.8030 | 0.8121    | 0.9175   |
+| 0.0025        | 14.0  | 3304 | 0.5992          | 0.8217     | 0.7913 | 0.8037    | 0.9155   |
+
+
+### 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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