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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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- wmt16 |
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metrics: |
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- bleu |
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model-index: |
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- name: t5-small-finetuned-ro-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: wmt16 |
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type: wmt16 |
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args: ro-en |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 13.4499 |
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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-small-finetuned-ro-to-en |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wmt16 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5877 |
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- Bleu: 13.4499 |
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- Gen Len: 17.5073 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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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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| 1.6167 | 0.05 | 2000 | 1.8649 | 9.7029 | 17.5753 | |
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| 1.4551 | 0.1 | 4000 | 1.7810 | 10.6382 | 17.5358 | |
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| 1.3723 | 0.16 | 6000 | 1.7369 | 11.1285 | 17.5158 | |
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| 1.3373 | 0.21 | 8000 | 1.7086 | 11.6173 | 17.5013 | |
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| 1.2935 | 0.26 | 10000 | 1.6890 | 12.0641 | 17.5038 | |
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| 1.2632 | 0.31 | 12000 | 1.6670 | 12.3012 | 17.5253 | |
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| 1.2463 | 0.37 | 14000 | 1.6556 | 12.3991 | 17.5153 | |
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| 1.2272 | 0.42 | 16000 | 1.6442 | 12.7392 | 17.4732 | |
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| 1.2052 | 0.47 | 18000 | 1.6328 | 12.8446 | 17.5143 | |
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| 1.1985 | 0.52 | 20000 | 1.6233 | 13.0892 | 17.4807 | |
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| 1.1821 | 0.58 | 22000 | 1.6153 | 13.1529 | 17.4952 | |
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| 1.1791 | 0.63 | 24000 | 1.6079 | 13.2964 | 17.5088 | |
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| 1.1698 | 0.68 | 26000 | 1.6038 | 13.3548 | 17.4842 | |
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| 1.154 | 0.73 | 28000 | 1.5957 | 13.3012 | 17.5053 | |
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| 1.1634 | 0.79 | 30000 | 1.5931 | 13.4203 | 17.5083 | |
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| 1.1487 | 0.84 | 32000 | 1.5893 | 13.3959 | 17.5123 | |
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| 1.1495 | 0.89 | 34000 | 1.5875 | 13.3745 | 17.4902 | |
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| 1.1458 | 0.94 | 36000 | 1.5877 | 13.4129 | 17.5043 | |
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| 1.1465 | 1.0 | 38000 | 1.5877 | 13.4499 | 17.5073 | |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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