End of training

README.md

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+---
+language:
+- nl
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- abc
+- generated_from_trainer
+datasets:
+- stsb_multi_mt
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-FinedTuned
+  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. -->
+
+# bert-base-uncased-FinedTuned
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3210
+- Accuracy: 0.1762
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- training_steps: 100
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| No log        | 0.0556 | 10   | 7.6479          | 0.1762   |
+| No log        | 0.1111 | 20   | 6.9937          | 0.1762   |
+| 8.2277        | 0.1667 | 30   | 6.2531          | 0.1762   |
+| 8.2277        | 0.2222 | 40   | 5.6151          | 0.1762   |
+| 6.019         | 0.2778 | 50   | 4.8978          | 0.1762   |
+| 6.019         | 0.3333 | 60   | 3.6924          | 0.1762   |
+| 6.019         | 0.3889 | 70   | 2.9463          | 0.1762   |
+| 3.6301        | 0.4444 | 80   | 2.5056          | 0.1762   |
+| 3.6301        | 0.5    | 90   | 2.3194          | 0.1762   |
+| 2.2789        | 0.5556 | 100  | 2.3210          | 0.1762   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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