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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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model-index: |
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- name: t5-finetuned-ar-to-arsl_test |
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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-arsl_test |
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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: 0.3309 |
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- Bleu1: 0.9310 |
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- Bleu2: 0.8974 |
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- Bleu3: 0.7219 |
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- Bleu4: 0.5884 |
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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 | Bleu1 | Bleu2 | Bleu3 | Bleu4 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:| |
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| No log | 1.0 | 59 | 0.4660 | 0.8440 | 0.7803 | 0.5955 | 0.4626 | |
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| No log | 2.0 | 118 | 0.3223 | 0.8966 | 0.8500 | 0.6689 | 0.5321 | |
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| No log | 2.99 | 177 | 0.3004 | 0.9170 | 0.8791 | 0.7022 | 0.5644 | |
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| No log | 3.99 | 236 | 0.2925 | 0.9205 | 0.8834 | 0.7071 | 0.5703 | |
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| No log | 4.99 | 295 | 0.3099 | 0.9223 | 0.8859 | 0.7090 | 0.5716 | |
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| No log | 5.99 | 354 | 0.2879 | 0.9244 | 0.8892 | 0.7125 | 0.5768 | |
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| No log | 6.99 | 413 | 0.2971 | 0.9280 | 0.8936 | 0.7176 | 0.5824 | |
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| No log | 8.0 | 473 | 0.2986 | 0.9254 | 0.8899 | 0.7136 | 0.5800 | |
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| 0.3874 | 9.0 | 532 | 0.3128 | 0.9293 | 0.8952 | 0.7204 | 0.5874 | |
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| 0.3874 | 10.0 | 591 | 0.3166 | 0.9316 | 0.8992 | 0.7242 | 0.5907 | |
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| 0.3874 | 10.99 | 650 | 0.3270 | 0.9303 | 0.8964 | 0.7214 | 0.5861 | |
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| 0.3874 | 11.99 | 709 | 0.3290 | 0.9304 | 0.8961 | 0.7223 | 0.5883 | |
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| 0.3874 | 12.99 | 768 | 0.3326 | 0.9296 | 0.8957 | 0.7216 | 0.5880 | |
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| 0.3874 | 13.99 | 827 | 0.3309 | 0.9294 | 0.8959 | 0.7208 | 0.5870 | |
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| 0.3874 | 14.97 | 885 | 0.3309 | 0.9310 | 0.8974 | 0.7219 | 0.5884 | |
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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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