Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("a2ran/kogpt2-wellness")
model = AutoModelForCausalLM.from_pretrained("a2ran/kogpt2-wellness")Quick Links
kogpt2-finetuned-chatbot
This model is a fine-tuned version of skt/kogpt2-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6311
'<\unused1>' ํ ํฐ์ ๊ธฐ์ค์ผ๋ก ์ง๋ฌธ, ๋ฐํ ๋ต๋ณ์ ๋๋ ์๋ตํ text generation pretrained ๋ชจ๋ธ์ ๋๋ค.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9794 | 1.0 | 4436 | 0.8402 |
| 0.7568 | 2.0 | 8872 | 0.6767 |
| 0.6748 | 3.0 | 13308 | 0.6311 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="a2ran/kogpt2-wellness")