Instructions to use ThuyNT03/CS221_DT_bartpho-add-accent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThuyNT03/CS221_DT_bartpho-add-accent with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ThuyNT03/CS221_DT_bartpho-add-accent") model = AutoModelForSeq2SeqLM.from_pretrained("ThuyNT03/CS221_DT_bartpho-add-accent") - Notebooks
- Google Colab
- Kaggle
CS336_bartpho-syllable-base_add-accent
This model is a fine-tuned version of vinai/bartpho-syllable-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: 5e-05
- train_batch_size: 12
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
- Downloads last month
- 7
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Model tree for ThuyNT03/CS221_DT_bartpho-add-accent
Base model
vinai/bartpho-syllable-base