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--- |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: VietAI/gpt-neo-1.3B-vietnamese-news |
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model-index: |
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- name: gpt-neo-1.3B-vietnamese-news_model_kaggle_test |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gpt-neo-1.3B-vietnamese-news_model_kaggle_test |
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This model is a fine-tuned version of [VietAI/gpt-neo-1.3B-vietnamese-news](https://huggingface.co/VietAI/gpt-neo-1.3B-vietnamese-news) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1194 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 15 | 4.1718 | |
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| No log | 2.0 | 30 | 3.6789 | |
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| No log | 3.0 | 45 | 3.2484 | |
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| No log | 4.0 | 60 | 2.8954 | |
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| No log | 5.0 | 75 | 2.6081 | |
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| No log | 6.0 | 90 | 2.3656 | |
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| No log | 7.0 | 105 | 2.1602 | |
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| No log | 8.0 | 120 | 1.9739 | |
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| No log | 9.0 | 135 | 1.8137 | |
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| No log | 10.0 | 150 | 1.6778 | |
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| No log | 11.0 | 165 | 1.5595 | |
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| No log | 12.0 | 180 | 1.4598 | |
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| No log | 13.0 | 195 | 1.3742 | |
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| No log | 14.0 | 210 | 1.3033 | |
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| No log | 15.0 | 225 | 1.2446 | |
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| No log | 16.0 | 240 | 1.1988 | |
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| No log | 17.0 | 255 | 1.1638 | |
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| No log | 18.0 | 270 | 1.1392 | |
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| No log | 19.0 | 285 | 1.1243 | |
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| No log | 20.0 | 300 | 1.1194 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
