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---
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 |