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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: finetuned_bert-base-uncased |
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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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# finetuned_bert-base-uncased |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0293 |
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- Accuracy: 0.6664 |
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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: 2e-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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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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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| No log | 1.0 | 204 | 1.0807 | 0.6586 | |
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| No log | 2.0 | 408 | 1.2250 | 0.6760 | |
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| 0.271 | 3.0 | 612 | 1.1975 | 0.6663 | |
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| 0.271 | 4.0 | 816 | 1.2170 | 0.6625 | |
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| 0.2395 | 5.0 | 1020 | 1.2817 | 0.6702 | |
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| 0.2395 | 6.0 | 1224 | 1.4138 | 0.6634 | |
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| 0.2395 | 7.0 | 1428 | 1.5268 | 0.6819 | |
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| 0.1661 | 8.0 | 1632 | 1.5753 | 0.6702 | |
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| 0.1661 | 9.0 | 1836 | 1.6794 | 0.6663 | |
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| 0.1349 | 10.0 | 2040 | 1.6416 | 0.6731 | |
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| 0.1349 | 11.0 | 2244 | 1.7056 | 0.6741 | |
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| 0.1349 | 12.0 | 2448 | 1.7374 | 0.6760 | |
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| 0.1159 | 13.0 | 2652 | 1.8817 | 0.6644 | |
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| 0.1159 | 14.0 | 2856 | 1.7318 | 0.6751 | |
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| 0.111 | 15.0 | 3060 | 1.8213 | 0.6712 | |
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| 0.111 | 16.0 | 3264 | 1.8347 | 0.6722 | |
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| 0.111 | 17.0 | 3468 | 1.8072 | 0.6780 | |
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| 0.0988 | 18.0 | 3672 | 1.8371 | 0.6770 | |
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| 0.0988 | 19.0 | 3876 | 1.8562 | 0.6741 | |
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| 0.0907 | 20.0 | 4080 | 1.8583 | 0.6741 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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