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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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- 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: BERT_large_with_preprocessing_grid_search
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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_with_preprocessing_grid_search
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0736
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- Precision: 0.0187
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- Recall: 0.125
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- F1: 0.0326
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- Accuracy: 0.1497
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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: 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: 10
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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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| 2.1138 | 1.0 | 510 | 2.0795 | 0.0041 | 0.125 | 0.0080 | 0.0329 |
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| 2.1114 | 2.0 | 1020 | 2.0853 | 0.0194 | 0.125 | 0.0336 | 0.1551 |
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| 2.106 | 3.0 | 1530 | 2.0806 | 0.0345 | 0.125 | 0.0541 | 0.2759 |
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| 2.1015 | 4.0 | 2040 | 2.0758 | 0.0284 | 0.125 | 0.0462 | 0.2268 |
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| 2.0997 | 5.0 | 2550 | 2.0808 | 0.0041 | 0.125 | 0.0080 | 0.0329 |
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| 2.0998 | 6.0 | 3060 | 2.0754 | 0.0284 | 0.125 | 0.0462 | 0.2268 |
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| 2.099 | 7.0 | 3570 | 2.0737 | 0.0194 | 0.125 | 0.0336 | 0.1551 |
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| 2.0945 | 8.0 | 4080 | 2.0812 | 0.0045 | 0.125 | 0.0086 | 0.0358 |
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| 2.0986 | 9.0 | 4590 | 2.0731 | 0.0187 | 0.125 | 0.0326 | 0.1497 |
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| 2.0958 | 10.0 | 5100 | 2.0736 | 0.0187 | 0.125 | 0.0326 | 0.1497 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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