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--- |
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base_model: UBC-NLP/AraT5v2-base-1024 |
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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: results_arat5_wiki |
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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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# results_arat5_wiki |
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This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co./UBC-NLP/AraT5v2-base-1024) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4401 |
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- Rouge1: 0.0905 |
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- Rouge2: 0.0 |
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- Rougel: 0.0915 |
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- Rougelsum: 0.0912 |
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- Gen Len: 19.0 |
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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: 0.0005 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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_steps: 250 |
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- num_epochs: 10 |
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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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| 7.7921 | 0.4757 | 500 | 6.2870 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 5.9839 | 0.9515 | 1000 | 5.5934 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 5.4311 | 1.4272 | 1500 | 5.0896 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 5.1245 | 1.9029 | 2000 | 4.7004 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 4.7258 | 2.3787 | 2500 | 4.3347 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 4.5072 | 2.8544 | 3000 | 4.0503 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 4.2388 | 3.3302 | 3500 | 3.8321 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 4.0817 | 3.8059 | 4000 | 3.6509 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.8843 | 4.2816 | 4500 | 3.4451 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.7958 | 4.7574 | 5000 | 3.3071 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.6397 | 5.2331 | 5500 | 3.1619 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.5658 | 5.7088 | 6000 | 3.0068 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.4171 | 6.1846 | 6500 | 2.9459 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.2697 | 6.6603 | 7000 | 2.8074 | 0.0842 | 0.0 | 0.0849 | 0.0844 | 19.0 | |
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| 3.3168 | 7.1361 | 7500 | 2.7153 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.1594 | 7.6118 | 8000 | 2.6676 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.0928 | 8.0875 | 8500 | 2.5849 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.0318 | 8.5633 | 9000 | 2.5152 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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| 3.0392 | 9.0390 | 9500 | 2.4849 | 0.0902 | 0.0 | 0.0911 | 0.0908 | 19.0 | |
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| 2.9917 | 9.5147 | 10000 | 2.4569 | 0.0768 | 0.0001 | 0.0774 | 0.0768 | 19.0 | |
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| 2.9281 | 9.9905 | 10500 | 2.4401 | 0.0905 | 0.0 | 0.0915 | 0.0912 | 19.0 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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