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--- |
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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_ro-finetuned-en-to-it |
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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: 19.6396 |
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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_ro-finetuned-en-to-it |
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This model is a fine-tuned version of [j0hngou/t5-base-finetuned-en-to-ro](https://huggingface.co/j0hngou/t5-base-finetuned-en-to-ro) on the ccmatrix dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4669 |
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- Bleu: 19.6396 |
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- Gen Len: 52.4247 |
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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 | 2.0942 | 5.6875 | 73.434 | |
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| 2.5108 | 2.0 | 564 | 1.9725 | 6.6631 | 72.6607 | |
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| 2.5108 | 3.0 | 846 | 1.9010 | 7.9227 | 67.01 | |
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| 2.1659 | 4.0 | 1128 | 1.8452 | 8.9935 | 65.1027 | |
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| 2.1659 | 5.0 | 1410 | 1.7979 | 9.4164 | 64.9827 | |
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| 2.0288 | 6.0 | 1692 | 1.7590 | 9.6035 | 66.6933 | |
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| 2.0288 | 7.0 | 1974 | 1.7264 | 10.7658 | 62.068 | |
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| 1.9238 | 8.0 | 2256 | 1.6955 | 11.5779 | 59.472 | |
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| 1.8435 | 9.0 | 2538 | 1.6729 | 12.7588 | 56.584 | |
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| 1.8435 | 10.0 | 2820 | 1.6541 | 13.3086 | 56.1153 | |
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| 1.775 | 11.0 | 3102 | 1.6337 | 13.8543 | 55.3307 | |
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| 1.775 | 12.0 | 3384 | 1.6148 | 14.3566 | 55.2853 | |
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| 1.7204 | 13.0 | 3666 | 1.5994 | 14.693 | 55.6607 | |
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| 1.7204 | 14.0 | 3948 | 1.5838 | 15.1284 | 55.5327 | |
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| 1.6705 | 15.0 | 4230 | 1.5742 | 15.6125 | 55.0087 | |
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| 1.632 | 16.0 | 4512 | 1.5600 | 15.9616 | 54.052 | |
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| 1.632 | 17.0 | 4794 | 1.5526 | 16.495 | 53.562 | |
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| 1.5868 | 18.0 | 5076 | 1.5392 | 16.4252 | 54.4613 | |
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| 1.5868 | 19.0 | 5358 | 1.5311 | 16.753 | 54.1853 | |
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| 1.5656 | 20.0 | 5640 | 1.5262 | 17.0308 | 54.2473 | |
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| 1.5656 | 21.0 | 5922 | 1.5186 | 17.3553 | 53.396 | |
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| 1.529 | 22.0 | 6204 | 1.5121 | 17.6177 | 53.472 | |
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| 1.529 | 23.0 | 6486 | 1.5058 | 17.6409 | 53.6847 | |
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| 1.5071 | 24.0 | 6768 | 1.5038 | 18.2009 | 53.2327 | |
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| 1.4903 | 25.0 | 7050 | 1.4962 | 18.4838 | 52.9587 | |
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| 1.4903 | 26.0 | 7332 | 1.4935 | 18.5545 | 52.688 | |
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| 1.4686 | 27.0 | 7614 | 1.4879 | 18.62 | 53.5 | |
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| 1.4686 | 28.0 | 7896 | 1.4850 | 19.0099 | 52.34 | |
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| 1.4511 | 29.0 | 8178 | 1.4813 | 19.0538 | 52.474 | |
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| 1.4511 | 30.0 | 8460 | 1.4787 | 18.89 | 53.0753 | |
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| 1.4364 | 31.0 | 8742 | 1.4756 | 19.2582 | 52.3587 | |
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| 1.4279 | 32.0 | 9024 | 1.4739 | 19.2973 | 52.69 | |
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| 1.4279 | 33.0 | 9306 | 1.4725 | 19.3624 | 52.694 | |
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| 1.4172 | 34.0 | 9588 | 1.4704 | 19.5421 | 52.1667 | |
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| 1.4172 | 35.0 | 9870 | 1.4689 | 19.4807 | 52.5487 | |
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| 1.4141 | 36.0 | 10152 | 1.4685 | 19.5972 | 52.2733 | |
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| 1.4141 | 37.0 | 10434 | 1.4676 | 19.5835 | 52.374 | |
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| 1.4058 | 38.0 | 10716 | 1.4674 | 19.6374 | 52.3447 | |
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| 1.4058 | 39.0 | 10998 | 1.4671 | 19.6105 | 52.5273 | |
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| 1.4027 | 40.0 | 11280 | 1.4669 | 19.6396 | 52.4247 | |
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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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