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--- |
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base_model: malmarjeh/t5-arabic-text-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: results |
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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 |
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This model is a fine-tuned version of [malmarjeh/t5-arabic-text-summarization](https://huggingface.co/malmarjeh/t5-arabic-text-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0104 |
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- Rouge1: 0.1382 |
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- Rouge2: 0.0187 |
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- Rougel: 0.1382 |
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- Rougelsum: 0.1382 |
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- Gen Len: 18.9404 |
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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: 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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 5 |
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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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| 0.0338 | 0.23 | 500 | 0.0175 | 0.1514 | 0.0297 | 0.1511 | 0.1518 | 18.9188 | |
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| 0.0566 | 0.46 | 1000 | 0.0161 | 0.1565 | 0.0388 | 0.157 | 0.1573 | 18.9188 | |
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| 0.0418 | 0.7 | 1500 | 0.0125 | 0.1372 | 0.0199 | 0.1375 | 0.1379 | 18.8105 | |
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| 0.0333 | 0.93 | 2000 | 0.0116 | 0.1443 | 0.0253 | 0.1448 | 0.1448 | 18.8051 | |
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| 0.0287 | 1.16 | 2500 | 0.0110 | 0.144 | 0.0192 | 0.1442 | 0.1442 | 19.0 | |
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| 0.0247 | 1.39 | 3000 | 0.0096 | 0.1511 | 0.024 | 0.1517 | 0.1518 | 19.0 | |
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| 0.0219 | 1.62 | 3500 | 0.0087 | 0.1463 | 0.0241 | 0.1462 | 0.1462 | 18.9747 | |
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| 0.021 | 1.86 | 4000 | 0.0104 | 0.1382 | 0.0187 | 0.1382 | 0.1382 | 18.9404 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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