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README.md
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---
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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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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: BERT_Text_classification_noisy
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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_Text_classification_noisy
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4823
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- Accuracy: 0.8880
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- F1: 0.8776
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- Precision: 0.8835
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- Recall: 0.8779
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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: 32
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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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- lr_scheduler_warmup_steps: 100
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 1.7338 | 0.24 | 50 | 1.4138 | 0.7076 | 0.6300 | 0.5892 | 0.6828 |
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| 0.9336 | 0.48 | 100 | 0.5276 | 0.8361 | 0.8305 | 0.8407 | 0.8303 |
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| 0.5885 | 0.71 | 150 | 0.4815 | 0.8603 | 0.8541 | 0.8583 | 0.8525 |
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| 0.6172 | 0.95 | 200 | 0.5176 | 0.8777 | 0.8648 | 0.8712 | 0.8664 |
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| 0.5229 | 1.19 | 250 | 0.4818 | 0.8809 | 0.8709 | 0.8769 | 0.8707 |
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| 0.4757 | 1.43 | 300 | 0.4845 | 0.8827 | 0.8720 | 0.8786 | 0.8722 |
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| 0.4286 | 1.67 | 350 | 0.4231 | 0.8854 | 0.8759 | 0.8776 | 0.8758 |
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| 0.4837 | 1.9 | 400 | 0.4763 | 0.8907 | 0.8794 | 0.8864 | 0.8799 |
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| 0.4031 | 2.14 | 450 | 0.4539 | 0.8880 | 0.8766 | 0.8833 | 0.8773 |
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| 0.4305 | 2.38 | 500 | 0.4775 | 0.8858 | 0.8752 | 0.8806 | 0.8755 |
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| 0.3538 | 2.62 | 550 | 0.4863 | 0.8880 | 0.8771 | 0.8853 | 0.8776 |
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| 0.325 | 2.86 | 600 | 0.4823 | 0.8880 | 0.8776 | 0.8835 | 0.8779 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.2
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