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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: BERT_Text_classification_noisy
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BERT_Text_classification_noisy
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4823
- Accuracy: 0.8880
- F1: 0.8776
- Precision: 0.8835
- Recall: 0.8779
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.7338 | 0.24 | 50 | 1.4138 | 0.7076 | 0.6300 | 0.5892 | 0.6828 |
| 0.9336 | 0.48 | 100 | 0.5276 | 0.8361 | 0.8305 | 0.8407 | 0.8303 |
| 0.5885 | 0.71 | 150 | 0.4815 | 0.8603 | 0.8541 | 0.8583 | 0.8525 |
| 0.6172 | 0.95 | 200 | 0.5176 | 0.8777 | 0.8648 | 0.8712 | 0.8664 |
| 0.5229 | 1.19 | 250 | 0.4818 | 0.8809 | 0.8709 | 0.8769 | 0.8707 |
| 0.4757 | 1.43 | 300 | 0.4845 | 0.8827 | 0.8720 | 0.8786 | 0.8722 |
| 0.4286 | 1.67 | 350 | 0.4231 | 0.8854 | 0.8759 | 0.8776 | 0.8758 |
| 0.4837 | 1.9 | 400 | 0.4763 | 0.8907 | 0.8794 | 0.8864 | 0.8799 |
| 0.4031 | 2.14 | 450 | 0.4539 | 0.8880 | 0.8766 | 0.8833 | 0.8773 |
| 0.4305 | 2.38 | 500 | 0.4775 | 0.8858 | 0.8752 | 0.8806 | 0.8755 |
| 0.3538 | 2.62 | 550 | 0.4863 | 0.8880 | 0.8771 | 0.8853 | 0.8776 |
| 0.325 | 2.86 | 600 | 0.4823 | 0.8880 | 0.8776 | 0.8835 | 0.8779 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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