---
license: apache-2.0
base_model: Langboat/mengzi-bert-base-fin
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1
  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. -->

# mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1

This model is a fine-tuned version of [Langboat/mengzi-bert-base-fin](https://huggingface.co/Langboat/mengzi-bert-base-fin) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2948
- Accuracy: 0.7241

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 38   | 0.6799          | 0.5517   |
| No log        | 2.0   | 76   | 0.6132          | 0.7241   |
| No log        | 3.0   | 114  | 0.6453          | 0.6207   |
| No log        | 4.0   | 152  | 0.7017          | 0.7586   |
| No log        | 5.0   | 190  | 0.9160          | 0.7241   |
| No log        | 6.0   | 228  | 1.0803          | 0.7586   |
| No log        | 7.0   | 266  | 1.1766          | 0.7241   |
| No log        | 8.0   | 304  | 1.1976          | 0.7586   |
| No log        | 9.0   | 342  | 1.2610          | 0.7241   |
| No log        | 10.0  | 380  | 1.2948          | 0.7241   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3