metadata
tags:
- Luc bat poem
- GPT2
- Causal-lm
model-index:
- name: PoetGPT_Vietnamese
results: []
language:
- vi
widget:
- text: <|startoftext|>ngày xuân
example_title: ngày xuân
Lục Bát AI Poet
How to generation with prompt?
Type:
<|startoftext|> + your_prompt
Examples:
<|startoftext|>ngày xuân
Usage:
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel
tokenizer = GPT2Tokenizer.from_pretrained('luanngo/PoetGPT')
model = GPT2LMHeadModel.from_pretrained('luanngo/PoetGPT')
prompt = "<|startoftext|>" + "ngày xuân"
input_ids = tokenizer.encode(prompt.lower(), return_tensors='pt')
max_length = 100
outputs = model.generate(input_ids,
do_sample=True,
max_length=max_length,
top_p=0.95,
temperature=1.0,
repetition_penalty=10.0,
num_beams=5,
early_stopping=True,
num_return_sequences=3)
for i, output in enumerate(outputs):
print(">> Generated text {}\n\n{}".format(i+1,
tokenizer.decode(output.tolist())))
print('\n---')
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-4
- train_batch_size: 64
- eval_batch_size: 64
- seed: 37
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6633 | 1.0 | 704 | 2.6718 |
| 2.5567 | 2.0 | 1408 | 2.5756 |
| 2.4885 | 3.0 | 2112 | 2.5283 |
| 2.3552 | 4.0 | 2816 | 2.4395 |
| 2.3084 | 5.0 | 3520 | 2.3811 |
| 2.2587 | 6.0 | 4224 | 2.3699 |
| 2.1938 | 7.0 | 4928 | 2.3470 |
| 2.1491 | 8.0 | 5632 | 2.3225 |
| 2.0623 | 9.0 | 6336 | 2.3276 |
| 2.0672 | 10.0 | 7040 | 2.3301 |
| 2.0293 | 11.0 | 7744 | 2.3186 |
| 1.9694 | 12.0 | 8448 | 2.3331 |
| 1.8658 | 13.0 | 9152 | 2.3565 |
| 1.8558 | 14.0 | 9856 | 2.3592 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.12.1