Instructions to use long292/bartpho-syllable-base-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use long292/bartpho-syllable-base-v3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("long292/bartpho-syllable-base-v3") model = AutoModelForSeq2SeqLM.from_pretrained("long292/bartpho-syllable-base-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
bartpho-syllable-base-v3
This model is a fine-tuned version of vinai/bartpho-syllable-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8996
- Bleu: 19.1417
- Gen Len: 17.69
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 1.9889 | 1.0 | 9155 | 1.8996 | 19.1417 | 17.69 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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vinai/bartpho-syllable-base