# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="ShynBui/vie_qa")# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("ShynBui/vie_qa")
model = AutoModelForQuestionAnswering.from_pretrained("ShynBui/vie_qa")Quick Links
vie_qa
This model is a fine-tuned version of ShynBui/vi_qa 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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ShynBui/vi_qa
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