---
license: gpl-3.0
base_model: ckiplab/albert-base-chinese
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-chinese
  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-base-chinese

This model is a fine-tuned version of [ckiplab/albert-base-chinese](https://huggingface.co/ckiplab/albert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6943
- F1: 0.5455
- Roc Auc: 0.5500
- Accuracy: 0.0

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 1    | 0.6943          | 0.5455 | 0.5500  | 0.0      |
| No log        | 2.0   | 2    | 0.6945          | 0.5455 | 0.5500  | 0.0      |
| No log        | 3.0   | 3    | 0.6947          | 0.5455 | 0.5500  | 0.0      |
| No log        | 4.0   | 4    | 0.6949          | 0.5455 | 0.5500  | 0.0      |
| No log        | 5.0   | 5    | 0.6949          | 0.5455 | 0.5500  | 0.0      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0