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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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datasets: |
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- ccmatrix |
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metrics: |
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- bleu |
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model-index: |
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- name: t5-base-finetuned-it-to-en |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: ccmatrix |
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type: ccmatrix |
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config: en-it |
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split: train[3000:12000] |
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args: en-it |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 26.0557 |
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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-it-to-en |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the ccmatrix dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7418 |
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- Bleu: 26.0557 |
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- Gen Len: 25.6033 |
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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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| No log | 1.0 | 282 | 2.0555 | 16.8117 | 26.9573 | |
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| 2.3228 | 2.0 | 564 | 1.9791 | 18.207 | 26.754 | |
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| 2.3228 | 3.0 | 846 | 1.9340 | 19.2206 | 26.6513 | |
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| 2.104 | 4.0 | 1128 | 1.8999 | 20.0802 | 26.5473 | |
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| 2.104 | 5.0 | 1410 | 1.8741 | 20.9222 | 26.4633 | |
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| 1.9952 | 6.0 | 1692 | 1.8511 | 21.3 | 26.4547 | |
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| 1.9952 | 7.0 | 1974 | 1.8361 | 21.9444 | 26.5227 | |
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| 1.9032 | 8.0 | 2256 | 1.8191 | 22.224 | 26.168 | |
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| 1.8342 | 9.0 | 2538 | 1.8074 | 22.7097 | 26.1573 | |
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| 1.8342 | 10.0 | 2820 | 1.7972 | 23.0299 | 26.2373 | |
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| 1.7718 | 11.0 | 3102 | 1.7898 | 23.5173 | 26.0447 | |
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| 1.7718 | 12.0 | 3384 | 1.7833 | 23.7157 | 26.0073 | |
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| 1.7268 | 13.0 | 3666 | 1.7785 | 23.8523 | 25.742 | |
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| 1.7268 | 14.0 | 3948 | 1.7725 | 23.979 | 25.88 | |
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| 1.6822 | 15.0 | 4230 | 1.7686 | 24.2126 | 25.8347 | |
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| 1.6386 | 16.0 | 4512 | 1.7639 | 24.4612 | 25.786 | |
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| 1.6386 | 17.0 | 4794 | 1.7605 | 24.6716 | 25.828 | |
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| 1.6047 | 18.0 | 5076 | 1.7549 | 24.9392 | 25.6493 | |
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| 1.6047 | 19.0 | 5358 | 1.7548 | 24.8965 | 25.6527 | |
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| 1.5778 | 20.0 | 5640 | 1.7537 | 24.9908 | 25.7827 | |
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| 1.5778 | 21.0 | 5922 | 1.7498 | 25.1397 | 25.6707 | |
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| 1.5413 | 22.0 | 6204 | 1.7472 | 25.2764 | 25.7373 | |
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| 1.5413 | 23.0 | 6486 | 1.7468 | 25.3103 | 25.6927 | |
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| 1.5249 | 24.0 | 6768 | 1.7471 | 25.3128 | 25.698 | |
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| 1.5052 | 25.0 | 7050 | 1.7449 | 25.4046 | 25.6813 | |
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| 1.5052 | 26.0 | 7332 | 1.7444 | 25.5513 | 25.7833 | |
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| 1.4825 | 27.0 | 7614 | 1.7448 | 25.4756 | 25.632 | |
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| 1.4825 | 28.0 | 7896 | 1.7432 | 25.6046 | 25.658 | |
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| 1.4665 | 29.0 | 8178 | 1.7422 | 25.6138 | 25.6907 | |
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| 1.4665 | 30.0 | 8460 | 1.7420 | 25.7196 | 25.7 | |
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| 1.4508 | 31.0 | 8742 | 1.7420 | 25.8684 | 25.618 | |
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| 1.4394 | 32.0 | 9024 | 1.7420 | 25.8188 | 25.6007 | |
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| 1.4394 | 33.0 | 9306 | 1.7417 | 25.9295 | 25.6113 | |
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| 1.4318 | 34.0 | 9588 | 1.7421 | 25.9842 | 25.614 | |
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| 1.4318 | 35.0 | 9870 | 1.7408 | 26.1045 | 25.5933 | |
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| 1.4244 | 36.0 | 10152 | 1.7409 | 26.0496 | 25.6327 | |
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| 1.4244 | 37.0 | 10434 | 1.7417 | 26.0595 | 25.6347 | |
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| 1.4139 | 38.0 | 10716 | 1.7420 | 26.0515 | 25.6047 | |
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| 1.4139 | 39.0 | 10998 | 1.7417 | 26.0727 | 25.616 | |
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| 1.4135 | 40.0 | 11280 | 1.7418 | 26.0557 | 25.6033 | |
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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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