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--- |
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license: apache-2.0 |
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base_model: bert-large-uncased |
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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: bert-large |
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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-large |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9621 |
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- Accuracy: 0.8887 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 256 |
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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 | 782 | 0.2848 | 0.8852 | |
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| 0.3133 | 2.0 | 1564 | 0.3038 | 0.8888 | |
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| 0.1751 | 3.0 | 2346 | 0.5035 | 0.8791 | |
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| 0.1057 | 4.0 | 3128 | 0.5942 | 0.885 | |
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| 0.1057 | 5.0 | 3910 | 0.5220 | 0.8764 | |
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| 0.0733 | 6.0 | 4692 | 0.6981 | 0.8823 | |
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| 0.0439 | 7.0 | 5474 | 0.6775 | 0.8833 | |
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| 0.0371 | 8.0 | 6256 | 0.6118 | 0.8891 | |
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| 0.0277 | 9.0 | 7038 | 0.7128 | 0.8864 | |
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| 0.0277 | 10.0 | 7820 | 0.7555 | 0.8868 | |
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| 0.0202 | 11.0 | 8602 | 0.7618 | 0.8888 | |
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| 0.0141 | 12.0 | 9384 | 0.7654 | 0.8842 | |
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| 0.0125 | 13.0 | 10166 | 0.8345 | 0.8867 | |
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| 0.0125 | 14.0 | 10948 | 0.8073 | 0.8844 | |
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| 0.0077 | 15.0 | 11730 | 0.7047 | 0.8887 | |
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| 0.0071 | 16.0 | 12512 | 0.8622 | 0.8891 | |
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| 0.004 | 17.0 | 13294 | 0.8655 | 0.8900 | |
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| 0.0031 | 18.0 | 14076 | 0.9096 | 0.8898 | |
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| 0.0031 | 19.0 | 14858 | 0.9454 | 0.8892 | |
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| 0.0016 | 20.0 | 15640 | 0.9621 | 0.8887 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.15.2 |
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