---
license: gpl-3.0
base_model: ckiplab/bert-base-chinese
tags:
- generated_from_trainer
model-index:
- name: clip-roberta-finetuned
  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. -->

# clip-roberta-finetuned

This model is a fine-tuned version of [ckiplab/bert-base-chinese](https://huggingface.co/ckiplab/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2379

## 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: 5e-05
- train_batch_size: 80
- eval_batch_size: 100
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6587        | 10.0  | 300  | 2.6721          |
| 0.5242        | 20.0  | 600  | 1.9951          |
| 0.1995        | 30.0  | 900  | 1.7767          |
| 0.1025        | 40.0  | 1200 | 1.6003          |
| 0.0609        | 50.0  | 1500 | 1.5020          |
| 0.042         | 60.0  | 1800 | 1.3372          |
| 0.0315        | 70.0  | 2100 | 1.3104          |
| 0.0271        | 80.0  | 2400 | 1.2715          |
| 0.0212        | 90.0  | 2700 | 1.2446          |
| 0.0202        | 100.0 | 3000 | 1.2379          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1