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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-base-finetuned-en-to-it-lrs-back |
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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-base-finetuned-en-to-it-lrs-back |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2426 |
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- Bleu: 27.5339 |
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- Gen Len: 50.356 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 1.997 | 1.0 | 1125 | 1.8350 | 10.7997 | 58.974 | |
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| 1.8185 | 2.0 | 2250 | 1.7013 | 13.8533 | 56.2727 | |
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| 1.6898 | 3.0 | 3375 | 1.6177 | 16.2932 | 53.914 | |
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| 1.5706 | 4.0 | 4500 | 1.5542 | 18.0621 | 53.4973 | |
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| 1.5151 | 5.0 | 5625 | 1.5086 | 19.4227 | 53.6307 | |
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| 1.468 | 6.0 | 6750 | 1.4707 | 20.8101 | 52.2427 | |
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| 1.4313 | 7.0 | 7875 | 1.4438 | 21.7975 | 51.8 | |
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| 1.383 | 8.0 | 9000 | 1.4182 | 22.4852 | 51.7193 | |
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| 1.3555 | 9.0 | 10125 | 1.3991 | 23.0898 | 51.448 | |
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| 1.3259 | 10.0 | 11250 | 1.3802 | 23.5277 | 51.6953 | |
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| 1.3041 | 11.0 | 12375 | 1.3656 | 23.9072 | 51.1547 | |
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| 1.2781 | 12.0 | 13500 | 1.3518 | 24.1772 | 51.3293 | |
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| 1.2577 | 13.0 | 14625 | 1.3394 | 24.4547 | 51.6307 | |
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| 1.24 | 14.0 | 15750 | 1.3312 | 24.9846 | 50.9827 | |
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| 1.2198 | 15.0 | 16875 | 1.3180 | 25.1942 | 51.042 | |
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| 1.2071 | 16.0 | 18000 | 1.3098 | 25.5082 | 50.6113 | |
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| 1.1948 | 17.0 | 19125 | 1.3024 | 25.523 | 50.782 | |
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| 1.1795 | 18.0 | 20250 | 1.2961 | 25.8367 | 50.7987 | |
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| 1.1691 | 19.0 | 21375 | 1.2904 | 25.9142 | 50.6667 | |
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| 1.159 | 20.0 | 22500 | 1.2824 | 26.2538 | 50.602 | |
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| 1.1504 | 21.0 | 23625 | 1.2794 | 26.2023 | 50.5987 | |
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| 1.1389 | 22.0 | 24750 | 1.2746 | 26.464 | 50.4593 | |
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| 1.1309 | 23.0 | 25875 | 1.2694 | 26.4899 | 50.5353 | |
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| 1.1185 | 24.0 | 27000 | 1.2676 | 26.8721 | 50.468 | |
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| 1.1126 | 25.0 | 28125 | 1.2635 | 26.8721 | 50.4693 | |
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| 1.1093 | 26.0 | 29250 | 1.2603 | 27.0334 | 50.334 | |
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| 1.104 | 27.0 | 30375 | 1.2569 | 27.2444 | 50.554 | |
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| 1.0988 | 28.0 | 31500 | 1.2535 | 27.2597 | 50.5367 | |
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| 1.0893 | 29.0 | 32625 | 1.2509 | 27.3268 | 50.42 | |
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| 1.0883 | 30.0 | 33750 | 1.2519 | 27.4412 | 50.4253 | |
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| 1.0802 | 31.0 | 34875 | 1.2479 | 27.3715 | 50.4247 | |
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| 1.0697 | 32.0 | 36000 | 1.2476 | 27.3871 | 50.5567 | |
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| 1.0729 | 33.0 | 37125 | 1.2457 | 27.4333 | 50.418 | |
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| 1.065 | 34.0 | 38250 | 1.2451 | 27.4571 | 50.4287 | |
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| 1.0649 | 35.0 | 39375 | 1.2451 | 27.5448 | 50.3393 | |
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| 1.0644 | 36.0 | 40500 | 1.2438 | 27.5387 | 50.2813 | |
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| 1.0624 | 37.0 | 41625 | 1.2423 | 27.5011 | 50.402 | |
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| 1.0617 | 38.0 | 42750 | 1.2434 | 27.5414 | 50.336 | |
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| 1.0606 | 39.0 | 43875 | 1.2429 | 27.5247 | 50.3387 | |
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| 1.0508 | 40.0 | 45000 | 1.2426 | 27.5339 | 50.356 | |
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### Framework versions |
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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 |
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