Instructions to use NIRVLab/bartede with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NIRVLab/bartede with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NIRVLab/bartede") model = AutoModelForSeq2SeqLM.from_pretrained("NIRVLab/bartede") - Notebooks
- Google Colab
- Kaggle
End of training
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README.md
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This model is a fine-tuned version of [vinai/bartpho-syllable](https://huggingface.co/vinai/bartpho-syllable) on an unknown dataset.
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It achieves the following results on the evaluation set:
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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| No log | 1.0 | 158 | 0.
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| No log | 2.0 | 316 | 0.
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| No log | 3.0 | 474 | 0.
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### Framework versions
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This model is a fine-tuned version of [vinai/bartpho-syllable](https://huggingface.co/vinai/bartpho-syllable) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5731
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 158 | 0.8921 |
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| No log | 2.0 | 316 | 0.7830 |
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| No log | 3.0 | 474 | 0.7182 |
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| 1.0152 | 4.0 | 632 | 0.6720 |
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| 1.0152 | 5.0 | 790 | 0.6444 |
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| 1.0152 | 6.0 | 948 | 0.6201 |
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| 0.6533 | 7.0 | 1106 | 0.6068 |
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| 0.6533 | 8.0 | 1264 | 0.5954 |
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| 0.6533 | 9.0 | 1422 | 0.5895 |
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| 0.5543 | 10.0 | 1580 | 0.5840 |
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| 0.5543 | 11.0 | 1738 | 0.5777 |
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| 0.5543 | 12.0 | 1896 | 0.5731 |
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| 0.4994 | 13.0 | 2054 | 0.5735 |
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| 0.4994 | 14.0 | 2212 | 0.5735 |
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| 0.4994 | 15.0 | 2370 | 0.5736 |
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### Framework versions
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