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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-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: 20.1194 |
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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 |
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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: 1.4830 |
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- Bleu: 20.1194 |
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- Gen Len: 51.456 |
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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 | 2.0137 | 6.5621 | 69.0227 | |
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| 2.4006 | 2.0 | 564 | 1.9278 | 7.2684 | 70.0333 | |
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| 2.4006 | 3.0 | 846 | 1.8712 | 8.6643 | 64.654 | |
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| 2.1423 | 4.0 | 1128 | 1.8223 | 9.3778 | 63.4453 | |
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| 2.1423 | 5.0 | 1410 | 1.7836 | 10.0151 | 63.778 | |
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| 2.0248 | 6.0 | 1692 | 1.7515 | 10.9865 | 62.224 | |
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| 2.0248 | 7.0 | 1974 | 1.7208 | 11.5089 | 61.2 | |
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| 1.9316 | 8.0 | 2256 | 1.6936 | 12.3755 | 60.1047 | |
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| 1.8584 | 9.0 | 2538 | 1.6731 | 12.8765 | 59.4427 | |
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| 1.8584 | 10.0 | 2820 | 1.6535 | 13.7278 | 57.6253 | |
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| 1.7949 | 11.0 | 3102 | 1.6360 | 14.2498 | 56.3913 | |
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| 1.7949 | 12.0 | 3384 | 1.6222 | 14.8795 | 55.346 | |
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| 1.7461 | 13.0 | 3666 | 1.6064 | 15.017 | 55.7473 | |
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| 1.7461 | 14.0 | 3948 | 1.5926 | 15.3093 | 56.0067 | |
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| 1.6998 | 15.0 | 4230 | 1.5803 | 15.6934 | 55.366 | |
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| 1.6635 | 16.0 | 4512 | 1.5707 | 16.3604 | 54.5413 | |
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| 1.6635 | 17.0 | 4794 | 1.5633 | 16.8086 | 53.824 | |
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| 1.621 | 18.0 | 5076 | 1.5515 | 17.1319 | 53.5927 | |
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| 1.621 | 19.0 | 5358 | 1.5450 | 17.5039 | 53.5167 | |
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| 1.6008 | 20.0 | 5640 | 1.5389 | 17.8012 | 53.6527 | |
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| 1.6008 | 21.0 | 5922 | 1.5314 | 17.7305 | 53.342 | |
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| 1.5656 | 22.0 | 6204 | 1.5259 | 18.1609 | 53.4033 | |
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| 1.5656 | 23.0 | 6486 | 1.5200 | 18.6506 | 52.226 | |
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| 1.5466 | 24.0 | 6768 | 1.5185 | 18.9433 | 52.2173 | |
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| 1.53 | 25.0 | 7050 | 1.5120 | 19.0978 | 52.022 | |
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| 1.53 | 26.0 | 7332 | 1.5083 | 19.1326 | 52.0527 | |
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| 1.5072 | 27.0 | 7614 | 1.5044 | 19.0854 | 52.2447 | |
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| 1.5072 | 28.0 | 7896 | 1.5002 | 19.372 | 51.7687 | |
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| 1.4926 | 29.0 | 8178 | 1.4977 | 19.5798 | 52.0327 | |
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| 1.4926 | 30.0 | 8460 | 1.4941 | 19.5161 | 51.9893 | |
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| 1.478 | 31.0 | 8742 | 1.4911 | 19.7821 | 51.534 | |
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| 1.47 | 32.0 | 9024 | 1.4897 | 19.7207 | 51.4787 | |
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| 1.47 | 33.0 | 9306 | 1.4888 | 19.8066 | 51.5407 | |
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| 1.4603 | 34.0 | 9588 | 1.4869 | 19.9036 | 51.398 | |
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| 1.4603 | 35.0 | 9870 | 1.4856 | 19.9575 | 51.352 | |
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| 1.4558 | 36.0 | 10152 | 1.4845 | 19.9513 | 51.4833 | |
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| 1.4558 | 37.0 | 10434 | 1.4840 | 20.0177 | 51.3027 | |
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| 1.4486 | 38.0 | 10716 | 1.4833 | 20.0644 | 51.484 | |
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| 1.4486 | 39.0 | 10998 | 1.4830 | 20.1001 | 51.5747 | |
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| 1.4452 | 40.0 | 11280 | 1.4830 | 20.1194 | 51.456 | |
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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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