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transliterated-akk-en-t5-small-instruct-small-context

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README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: AraT5v2-base-1024-p-l-akk-en-20240801-201225
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+ results: []
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+ ---
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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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+
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+ # AraT5v2-base-1024-p-l-akk-en-20240801-201225
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0402
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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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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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:------:|:---------------:|
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+ | 0.0561 | 0.0552 | 2500 | 0.0493 |
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+ | 0.0511 | 0.1105 | 5000 | 0.0501 |
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+ | 0.0475 | 0.1657 | 7500 | 0.0499 |
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+ | 0.0465 | 0.2210 | 10000 | 0.0499 |
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+ | 0.0417 | 0.2762 | 12500 | 0.0495 |
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+ | 0.0528 | 0.3314 | 15000 | 0.0497 |
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+ | 0.0523 | 0.3867 | 17500 | 0.0492 |
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+ | 0.0492 | 0.4419 | 20000 | 0.0497 |
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+ | 0.0468 | 0.4972 | 22500 | 0.0488 |
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+ | 0.0515 | 0.5524 | 25000 | 0.0489 |
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+ | 0.0522 | 0.6076 | 27500 | 0.0487 |
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+ | 0.0522 | 0.6629 | 30000 | 0.0489 |
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+ | 0.0544 | 0.7181 | 32500 | 0.0486 |
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+ | 0.0466 | 0.7734 | 35000 | 0.0488 |
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+ | 0.0546 | 0.8286 | 37500 | 0.0491 |
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+ | 0.0558 | 0.8838 | 40000 | 0.0486 |
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+ | 0.0532 | 0.9391 | 42500 | 0.0484 |
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+ | 0.049 | 0.9943 | 45000 | 0.0484 |
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+ | 0.049 | 1.0496 | 47500 | 0.0487 |
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+ | 0.0429 | 1.1048 | 50000 | 0.0483 |
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+ | 0.0549 | 1.1600 | 52500 | 0.0482 |
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+ | 0.047 | 1.2153 | 55000 | 0.0480 |
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+ | 0.0446 | 1.2705 | 57500 | 0.0477 |
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+ | 0.0583 | 1.3258 | 60000 | 0.0478 |
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+ | 0.0471 | 1.3810 | 62500 | 0.0477 |
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+ | 0.0549 | 1.4362 | 65000 | 0.0475 |
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+ | 0.0441 | 1.4915 | 67500 | 0.0476 |
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+ | 0.0467 | 1.5467 | 70000 | 0.0471 |
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+ | 0.0434 | 1.6020 | 72500 | 0.0467 |
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+ | 0.0522 | 1.6572 | 75000 | 0.0471 |
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+ | 0.0513 | 1.7124 | 77500 | 0.0469 |
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+ | 0.0492 | 1.7677 | 80000 | 0.0465 |
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+ | 0.0428 | 1.8229 | 82500 | 0.0466 |
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+ | 0.0479 | 1.8782 | 85000 | 0.0461 |
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+ | 0.0522 | 1.9334 | 87500 | 0.0463 |
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+ | 0.0503 | 1.9886 | 90000 | 0.0462 |
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+ | 0.0378 | 2.0439 | 92500 | 0.0463 |
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+ | 0.0442 | 2.0991 | 95000 | 0.0462 |
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+ | 0.0378 | 2.2096 | 100000 | 0.0460 |
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+ | 0.0445 | 3.0382 | 137500 | 0.0447 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0.dev0
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+ - Pytorch 2.5.0.dev20240625
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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