---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-chinese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_hw1_model
  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. -->

# my_awesome_hw1_model

This model is a fine-tuned version of [google-bert/bert-base-chinese](https://huggingface.co/google-bert/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3432
- Accuracy: 0.9511

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4023        | 1.0   | 10857 | 0.2515          | 0.9472   |
| 0.2345        | 2.0   | 21714 | 0.3472          | 0.9472   |
| 0.044         | 3.0   | 32571 | 0.3432          | 0.9511   |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4