---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine-tune-bert-stock-thai
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine-tune-bert-stock-thai

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1502
- Accuracy: 0.3597

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0972        | 1.0   | 450  | 1.0915          | 0.3606   |
| 1.0916        | 2.0   | 900  | 1.0926          | 0.3686   |
| 1.0813        | 3.0   | 1350 | 1.1004          | 0.3739   |
| 1.0671        | 4.0   | 1800 | 1.1064          | 0.3619   |
| 1.0376        | 5.0   | 2250 | 1.1372          | 0.3628   |
| 1.0158        | 6.0   | 2700 | 1.1502          | 0.3597   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1