Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use yeye776/OndeviceAI-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeye776/OndeviceAI-base-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yeye776/OndeviceAI-base-v2") model = AutoModelForSeq2SeqLM.from_pretrained("yeye776/OndeviceAI-base-v2") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-4.0 | |
| base_model: paust/pko-t5-base | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: OndeviceAI-base-v2 | |
| results: [] | |
| <!-- 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. --> | |
| # OndeviceAI-base-v2 | |
| This model is a fine-tuned version of [paust/pko-t5-base](https://huggingface.co/paust/pko-t5-base) on the None dataset. | |
| ## 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: 0.0007 | |
| - train_batch_size: 4 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 8 | |
| - total_train_batch_size: 32 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.06 | |
| - num_epochs: 20 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.37.2 | |
| - Pytorch 2.2.0+cu121 | |
| - Datasets 2.16.1 | |
| - Tokenizers 0.15.1 | |