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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_with_preprocessing_grid_search
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_with_preprocessing_grid_search
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9072
- Precision: 0.8332
- Recall: 0.8192
- F1: 0.8259
- Accuracy: 0.8660
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0741 | 1.0 | 510 | 0.6328 | 0.7761 | 0.8093 | 0.7820 | 0.8292 |
| 0.465 | 2.0 | 1020 | 0.5751 | 0.8326 | 0.8237 | 0.8265 | 0.8625 |
| 0.2979 | 3.0 | 1530 | 0.5442 | 0.8285 | 0.8482 | 0.8370 | 0.8719 |
| 0.2312 | 4.0 | 2040 | 0.6811 | 0.8434 | 0.8298 | 0.8350 | 0.8665 |
| 0.1609 | 5.0 | 2550 | 0.6873 | 0.8216 | 0.8338 | 0.8271 | 0.8635 |
| 0.14 | 6.0 | 3060 | 0.8476 | 0.8386 | 0.8175 | 0.8265 | 0.8640 |
| 0.1135 | 7.0 | 3570 | 0.8456 | 0.8302 | 0.8202 | 0.8249 | 0.8630 |
| 0.0973 | 8.0 | 4080 | 0.8595 | 0.8307 | 0.8186 | 0.8243 | 0.8625 |
| 0.0758 | 9.0 | 4590 | 0.8828 | 0.8306 | 0.8201 | 0.8251 | 0.8655 |
| 0.0669 | 10.0 | 5100 | 0.9072 | 0.8332 | 0.8192 | 0.8259 | 0.8660 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3