End of training

README.md

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+---
+license: mit
+base_model: Tommert25/robbert0410_lrate7.5b32
+tags:
+- generated_from_trainer
+metrics:
+- recall
+- accuracy
+model-index:
+- name: robbert1010_lrate7.5b32
+  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. -->
+
+# robbert1010_lrate7.5b32
+
+This model is a fine-tuned version of [Tommert25/robbert0410_lrate7.5b32](https://huggingface.co/Tommert25/robbert0410_lrate7.5b32) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5187
+- Precisions: 0.8552
+- Recall: 0.7999
+- F-measure: 0.8232
+- Accuracy: 0.9157
+
+## 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: 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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.0496        | 1.0   | 118  | 0.5283          | 0.8488     | 0.7962 | 0.8132    | 0.9092   |
+| 0.0474        | 2.0   | 236  | 0.4726          | 0.7961     | 0.7965 | 0.7931    | 0.9075   |
+| 0.026         | 3.0   | 354  | 0.5187          | 0.8552     | 0.7999 | 0.8232    | 0.9157   |
+| 0.0145        | 4.0   | 472  | 0.5150          | 0.8372     | 0.7791 | 0.7998    | 0.9116   |
+| 0.0088        | 5.0   | 590  | 0.5250          | 0.8372     | 0.7818 | 0.8021    | 0.9141   |
+| 0.007         | 6.0   | 708  | 0.5299          | 0.8468     | 0.7849 | 0.8072    | 0.9162   |
+
+
+### 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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