---
license: apache-2.0
base_model: Langboat/mengzi-bert-base-fin
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSE50-12
  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-wallstreetcn-morning-news-market-overview-SSE50-12

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: 1.9030
- Accuracy: 0.7879

## 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   | 34   | 2.2065          | 0.6667   |
| No log        | 2.0   | 68   | 2.7159          | 0.7273   |
| No log        | 3.0   | 102  | 2.6006          | 0.6970   |
| No log        | 4.0   | 136  | 2.2278          | 0.7273   |
| No log        | 5.0   | 170  | 3.0872          | 0.6667   |
| No log        | 6.0   | 204  | 1.7348          | 0.7273   |
| No log        | 7.0   | 238  | 1.8437          | 0.7879   |
| No log        | 8.0   | 272  | 1.7299          | 0.7576   |
| No log        | 9.0   | 306  | 1.9420          | 0.7879   |
| No log        | 10.0  | 340  | 1.9030          | 0.7879   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3