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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: 14apr-bert-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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# 14apr-bert-uncased |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1141 |
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- Precision: 0.9797 |
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- Recall: 0.9796 |
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- F1: 0.9797 |
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- Accuracy: 0.9774 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1405 | 1.0 | 2500 | 0.1016 | 0.9731 | 0.9761 | 0.9746 | 0.9721 | |
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| 0.0994 | 2.0 | 5000 | 0.0939 | 0.9776 | 0.9774 | 0.9775 | 0.9750 | |
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| 0.0731 | 3.0 | 7500 | 0.0968 | 0.9783 | 0.9790 | 0.9787 | 0.9767 | |
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| 0.045 | 4.0 | 10000 | 0.1075 | 0.9790 | 0.9798 | 0.9794 | 0.9773 | |
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| 0.035 | 5.0 | 12500 | 0.1141 | 0.9797 | 0.9796 | 0.9797 | 0.9774 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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