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--- |
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license: apache-2.0 |
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base_model: PRAli22/arat5-arabic-dialects-translation |
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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: t5-finetuned-ar-to-arsl2 |
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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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# t5-finetuned-ar-to-arsl2 |
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This model is a fine-tuned version of [PRAli22/arat5-arabic-dialects-translation](https://huggingface.co./PRAli22/arat5-arabic-dialects-translation) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3244 |
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- Rouge1: 0.0 |
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- Rouge2: 0.0 |
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- Rougel: 0.0 |
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- Rougelsum: 0.0 |
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- Gen Len: 5.2892 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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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: 15 |
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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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| No log | 0.99 | 78 | 0.4098 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2132 | |
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| No log | 1.99 | 157 | 0.3022 | 0.0 | 0.0 | 0.0 | 0.0 | 5.248 | |
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| No log | 2.99 | 236 | 0.2753 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2655 | |
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| No log | 3.99 | 315 | 0.2742 | 0.0 | 0.0 | 0.0 | 0.0 | 5.275 | |
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| No log | 5.0 | 394 | 0.2730 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2845 | |
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| No log | 6.0 | 473 | 0.2821 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2805 | |
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| 0.4176 | 7.0 | 552 | 0.2923 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2868 | |
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| 0.4176 | 8.0 | 631 | 0.2977 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2892 | |
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| 0.4176 | 8.99 | 709 | 0.2937 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2964 | |
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| 0.4176 | 9.99 | 788 | 0.3020 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2916 | |
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| 0.4176 | 10.99 | 867 | 0.3177 | 0.0 | 0.0 | 0.0 | 0.0 | 5.294 | |
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| 0.4176 | 11.99 | 946 | 0.3186 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2916 | |
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| 0.0879 | 13.0 | 1025 | 0.3255 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2884 | |
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| 0.0879 | 14.0 | 1104 | 0.3241 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2868 | |
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| 0.0879 | 14.83 | 1170 | 0.3244 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2892 | |
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### Framework versions |
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- Transformers 4.39.3 |
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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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