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# CN_BERT_Sci

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: 0.0088
- F1: {'f1': 0.9980007996801279}
- Accuracy: {'accuracy': 0.998}

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1                         | Accuracy             |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------:|:--------------------:|
| 0.3819        | 0.09  | 1000  | 0.3378          | {'f1': 0.7968977217644208} | {'accuracy': 0.7905} |
| 0.2709        | 0.18  | 2000  | 0.2719          | {'f1': 0.92162615255658}   | {'accuracy': 0.9252} |
| 0.169         | 0.27  | 3000  | 0.0888          | {'f1': 0.9760964045831687} | {'accuracy': 0.9758} |
| 0.0963        | 0.36  | 4000  | 0.0350          | {'f1': 0.991297389216765}  | {'accuracy': 0.9913} |
| 0.0499        | 0.44  | 5000  | 0.0260          | {'f1': 0.9937381969983102} | {'accuracy': 0.9937} |
| 0.0344        | 0.53  | 6000  | 0.0170          | {'f1': 0.9963048037551183} | {'accuracy': 0.9963} |
| 0.0307        | 0.62  | 7000  | 0.0213          | {'f1': 0.9957991598319663} | {'accuracy': 0.9958} |
| 0.036         | 0.71  | 8000  | 0.0105          | {'f1': 0.997700689793062}  | {'accuracy': 0.9977} |
| 0.0209        | 0.8   | 9000  | 0.0106          | {'f1': 0.9981032245183188} | {'accuracy': 0.9981} |
| 0.0253        | 0.89  | 10000 | 0.0089          | {'f1': 0.9981024667931688} | {'accuracy': 0.9981} |
| 0.0231        | 0.98  | 11000 | 0.0088          | {'f1': 0.9980007996801279} | {'accuracy': 0.998}  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "CN_BERT_Sci", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us