---
license: unknown
base_model: openthaigpt/openthaigpt-1.0.0-beta-7b-chat-ckpt-hf
tags:
- generated_from_trainer
model-index:
- name: out
  results: []
language:
- th
pipeline_tag: text-generation
datasets:
- allenai/MADLAD-400
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# ping98k/th-7b-20gb-base

This model is a continue pre-training version of [openthaigpt/openthaigpt-1.0.0-beta-7b-chat-ckpt-hf](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-7b-chat-ckpt-hf) on the 20GB Thai dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5721

## Inference with Pipeline

```python
import torch
from transformers import pipeline
text_generator = pipeline("text-generation", model="ping98k/th-7b-20gb-base", torch_dtype=torch.bfloat16, device_map="auto")
print(text_generator("แบบจำลองทางวิทยาศาสตร์ (scientific modeling) คือ", max_length=50))
```

## 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: 0.00015
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.0347        | 0.0   | 1     | 4.0530          |
| 2.2753        | 0.05  | 1179  | 2.2083          |
| 2.1613        | 0.1   | 2358  | 2.0422          |
| 2.0696        | 0.15  | 3537  | 1.9526          |
| 1.945         | 0.2   | 4716  | 1.8886          |
| 1.6807        | 0.25  | 5895  | 1.8340          |
| 1.5838        | 0.3   | 7074  | 1.7961          |
| 1.7497        | 0.35  | 8253  | 1.7548          |
| 1.535         | 0.4   | 9432  | 1.7237          |
| 1.9632        | 0.45  | 10611 | 1.6878          |
| 1.9091        | 0.5   | 11790 | 1.6631          |
| 1.6837        | 0.55  | 12969 | 1.6344          |
| 1.7054        | 0.6   | 14148 | 1.6131          |
| 1.463         | 0.65  | 15327 | 1.5980          |
| 1.5538        | 0.7   | 16506 | 1.5853          |
| 1.5095        | 0.75  | 17685 | 1.5780          |
| 1.7322        | 0.8   | 18864 | 1.5742          |
| 1.5645        | 0.85  | 20043 | 1.5727          |
| 1.72          | 0.9   | 21222 | 1.5722          |
| 1.5882        | 0.95  | 22401 | 1.5721          |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1