ping98k/th-7b-20gb-base

This model is a continue pre-training version of 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

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