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t5-small-finetuned-en-to-it-hrs

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: t5-small-finetuned-en-to-it-hrs
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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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+ # t5-small-finetuned-en-to-it-hrs
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1558
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+ - Bleu: 9.8991
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+ - Gen Len: 51.8287
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 40
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
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+ | 2.0084 | 1.0 | 1125 | 2.8804 | 4.4102 | 67.6067 |
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+ | 1.7918 | 2.0 | 2250 | 2.7757 | 6.1959 | 58.0313 |
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+ | 1.6944 | 3.0 | 3375 | 2.6845 | 6.9152 | 55.6953 |
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+ | 1.5955 | 4.0 | 4500 | 2.6219 | 7.3056 | 54.8213 |
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+ | 1.5304 | 5.0 | 5625 | 2.5659 | 7.9427 | 53.4173 |
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+ | 1.52 | 6.0 | 6750 | 2.5249 | 8.2049 | 53.678 |
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+ | 1.4934 | 7.0 | 7875 | 2.4853 | 8.6612 | 52.304 |
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+ | 1.4518 | 8.0 | 9000 | 2.4522 | 8.7991 | 52.6467 |
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+ | 1.4393 | 9.0 | 10125 | 2.4353 | 8.8251 | 52.7047 |
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+ | 1.4196 | 10.0 | 11250 | 2.4027 | 9.01 | 52.5387 |
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+ | 1.405 | 11.0 | 12375 | 2.3797 | 9.1513 | 52.0273 |
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+ | 1.3741 | 12.0 | 13500 | 2.3590 | 9.2401 | 52.3373 |
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+ | 1.3693 | 13.0 | 14625 | 2.3378 | 9.3611 | 52.1507 |
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+ | 1.3638 | 14.0 | 15750 | 2.3226 | 9.4213 | 52.2813 |
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+ | 1.3366 | 15.0 | 16875 | 2.3071 | 9.5199 | 52.1507 |
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+ | 1.3294 | 16.0 | 18000 | 2.2943 | 9.5296 | 51.9587 |
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+ | 1.3258 | 17.0 | 19125 | 2.2788 | 9.6231 | 51.5807 |
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+ | 1.3152 | 18.0 | 20250 | 2.2693 | 9.6586 | 51.8933 |
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+ | 1.3023 | 19.0 | 21375 | 2.2543 | 9.6762 | 51.5733 |
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+ | 1.3061 | 20.0 | 22500 | 2.2451 | 9.6926 | 51.6727 |
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+ | 1.3004 | 21.0 | 23625 | 2.2344 | 9.773 | 51.6527 |
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+ | 1.2839 | 22.0 | 24750 | 2.2242 | 9.7973 | 51.8113 |
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+ | 1.2869 | 23.0 | 25875 | 2.2161 | 9.8177 | 51.9073 |
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+ | 1.2819 | 24.0 | 27000 | 2.2115 | 9.8183 | 51.6707 |
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+ | 1.2642 | 25.0 | 28125 | 2.2037 | 9.7645 | 52.0853 |
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+ | 1.2685 | 26.0 | 29250 | 2.1984 | 9.7764 | 51.6927 |
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+ | 1.2609 | 27.0 | 30375 | 2.1934 | 9.7205 | 51.9647 |
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+ | 1.2585 | 28.0 | 31500 | 2.1834 | 9.8116 | 51.7373 |
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+ | 1.2564 | 29.0 | 32625 | 2.1811 | 9.8547 | 51.8553 |
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+ | 1.2563 | 30.0 | 33750 | 2.1766 | 9.8346 | 51.7293 |
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+ | 1.258 | 31.0 | 34875 | 2.1748 | 9.8204 | 51.6747 |
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+ | 1.2391 | 32.0 | 36000 | 2.1708 | 9.8485 | 51.7647 |
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+ | 1.2364 | 33.0 | 37125 | 2.1644 | 9.8503 | 51.6713 |
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+ | 1.2436 | 34.0 | 38250 | 2.1629 | 9.8457 | 51.76 |
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+ | 1.2408 | 35.0 | 39375 | 2.1614 | 9.8899 | 51.6893 |
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+ | 1.2564 | 36.0 | 40500 | 2.1591 | 9.8867 | 51.706 |
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+ | 1.2318 | 37.0 | 41625 | 2.1575 | 9.866 | 51.782 |
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+ | 1.2423 | 38.0 | 42750 | 2.1570 | 9.8756 | 51.8933 |
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+ | 1.2399 | 39.0 | 43875 | 2.1558 | 9.8871 | 51.7967 |
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+ | 1.2339 | 40.0 | 45000 | 2.1558 | 9.8991 | 51.8287 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.22.1
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+ - Pytorch 1.12.1
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+ - Datasets 2.5.1
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+ - Tokenizers 0.11.0