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# CN_BERT_Digit

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: 0.0264
- F1: {'f1': 0.9936038376973816}
- Accuracy: {'accuracy': 0.9936}

## 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             |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------:|:--------------------:|
| 0.4023        | 0.09  | 1000  | 0.5834          | {'f1': 0.7928479381443299} | {'accuracy': 0.7428} |
| 0.269         | 0.18  | 2000  | 0.2556          | {'f1': 0.8676012461059189} | {'accuracy': 0.881}  |
| 0.1879        | 0.27  | 3000  | 0.1296          | {'f1': 0.9648982848025529} | {'accuracy': 0.9648} |
| 0.142         | 0.36  | 4000  | 0.1022          | {'f1': 0.9740272663946662} | {'accuracy': 0.9739} |
| 0.1172        | 0.44  | 5000  | 0.0724          | {'f1': 0.979466322785438}  | {'accuracy': 0.9793} |
| 0.1044        | 0.53  | 6000  | 0.1166          | {'f1': 0.9756195043964828} | {'accuracy': 0.9756} |
| 0.0948        | 0.62  | 7000  | 0.0538          | {'f1': 0.98813441021039}   | {'accuracy': 0.9881} |
| 0.075         | 0.71  | 8000  | 0.0444          | {'f1': 0.9892989298929893} | {'accuracy': 0.9893} |
| 0.0667        | 0.8   | 9000  | 0.0427          | {'f1': 0.9911168779319294} | {'accuracy': 0.9911} |
| 0.0667        | 0.89  | 10000 | 0.0448          | {'f1': 0.9908384783907588} | {'accuracy': 0.9908} |
| 0.0668        | 0.98  | 11000 | 0.0264          | {'f1': 0.9936038376973816} | {'accuracy': 0.9936} |


### 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_Digit", "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