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--- |
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language: |
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- nl |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- abc |
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- generated_from_trainer |
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datasets: |
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- stsb_multi_mt |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-base-uncased-FinedTuned |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-uncased-FinedTuned |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6888 |
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- Accuracy: 0.1762 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 15000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:| |
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| 0.1203 | 5.5556 | 1000 | 2.7894 | 0.1762 | |
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| 0.089 | 11.1111 | 2000 | 2.7816 | 0.1762 | |
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| 0.095 | 16.6667 | 3000 | 2.7732 | 0.1762 | |
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| 0.0818 | 22.2222 | 4000 | 2.7201 | 0.1762 | |
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| 0.0786 | 27.7778 | 5000 | 2.6378 | 0.1762 | |
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| 0.0816 | 33.3333 | 6000 | 2.7167 | 0.1762 | |
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| 0.0795 | 38.8889 | 7000 | 2.6429 | 0.1762 | |
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| 0.0978 | 44.4444 | 8000 | 2.6964 | 0.1762 | |
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| 0.1006 | 50.0 | 9000 | 2.7168 | 0.1762 | |
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| 0.171 | 55.5556 | 10000 | 2.7183 | 0.1762 | |
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| 0.1185 | 61.1111 | 11000 | 2.6737 | 0.1762 | |
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| 0.1648 | 66.6667 | 12000 | 2.6573 | 0.1762 | |
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| 0.1365 | 72.2222 | 13000 | 2.6944 | 0.1762 | |
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| 0.1298 | 77.7778 | 14000 | 2.6950 | 0.1762 | |
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| 0.1832 | 83.3333 | 15000 | 2.6888 | 0.1762 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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