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Simple_VieQA – AI Model by ZycckZ | AlphaNeural AI
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ZycckZ
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Simple_VieQA
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transformers
tensorboard
safetensors
bert
question-answering
generated_from_trainer
vi
taidng/UIT-ViQuAD2.0
ZycckZ/Zk1-QA-VN-test
finetune
cc-by-sa-4.0
endpoints_compatible
us
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Model card
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Zk1-QA-VN-test2 (ZycckZ/Simple_VieQA)
This model is a fine-tuned version of
ZycckZ/Zk1-QA-VN-test
and
taidng/UIT-ViQuAD2
dataset.
It achieves the following results on the evaluation set:
Loss: 1.8800
Exact Match (EM): 70.07
F1 Score: 82.34
Model description
This model now much better than the model before (
ZycckZ/Zk1-QA-VN-test
).
Intended uses & limitations
Create a simple chatbot QA 🤗
Just for Vietnamese QA system
Training and evaluation data
Training:
taidng/UIT-ViQuAD2.0 - "train"
taidng/UIT-ViQuAD2.0 - "validation"
taidng/UIT-ViQuAD2.0 - "test"
Evaluation:
taidng/UIT-ViQuAD2.0 - "validation"
Training procedure
Based on Question Answering HuggingFace 🤗
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
1.171
1.0
2226
1.0648
0.8499
2.0
4452
1.1054
0.5862
3.0
6678
1.2583
0.4082
4.0
8904
1.5642
0.2835
5.0
11130
1.8800
Framework versions
Transformers 4.52.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
