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--- |
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license: mit |
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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: finetune-newwiki-summarization-ver1 |
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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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# finetune-newwiki-summarization-ver1 |
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This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4720 |
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- Rouge1: 48.6293 |
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- Rouge2: 25.6053 |
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- Rougel: 35.2967 |
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- Rougelsum: 37.4842 |
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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: 1e-05 |
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- train_batch_size: 4 |
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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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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 10 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 0.7106 | 1.0 | 1980 | 0.5006 | 46.5921 | 22.8276 | 33.1994 | 35.6330 | |
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| 0.621 | 2.0 | 3960 | 0.4774 | 47.4426 | 24.1508 | 34.1315 | 36.5692 | |
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| 0.5607 | 3.0 | 5940 | 0.4690 | 48.1503 | 24.7217 | 34.5071 | 36.7568 | |
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| 0.5241 | 4.0 | 7920 | 0.4673 | 48.2480 | 25.0604 | 34.4937 | 36.9301 | |
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| 0.499 | 5.0 | 9900 | 0.4678 | 48.1659 | 25.1857 | 34.9460 | 37.1931 | |
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| 0.4592 | 6.0 | 11880 | 0.4694 | 48.5839 | 25.5925 | 35.2301 | 37.5352 | |
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| 0.4535 | 7.0 | 13860 | 0.4720 | 48.6293 | 25.6053 | 35.2967 | 37.4842 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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