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--- |
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license: mit |
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base_model: VietAI/vit5-large-vietnews-summarization |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: finetuned-news_summarization_vi |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/minhquy16/huggingface/runs/4usld66u) |
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# finetuned-news_summarization_vi |
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This model is a fine-tuned version of [VietAI/vit5-large-vietnews-summarization](https://huggingface.co/VietAI/vit5-large-vietnews-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2271 |
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- Rouge1: 0.253 |
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- Rouge2: 0.1919 |
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- Rougel: 0.2233 |
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- Rougelsum: 0.2233 |
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- Gen Len: 18.496 |
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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: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 4 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.2561 | 1.0 | 65361 | 0.2342 | 0.248 | 0.1883 | 0.2192 | 0.2192 | 18.274 | |
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| 0.1831 | 2.0 | 130722 | 0.2271 | 0.253 | 0.1919 | 0.2233 | 0.2233 | 18.496 | |
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### Framework versions |
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- Transformers 4.43.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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