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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-de-to-en-lr1e-4 |
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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: de-en |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 11.427 |
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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-de-to-en-lr1e-4 |
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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: 1.8228 |
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- Bleu: 11.427 |
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- Gen Len: 17.2674 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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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 | 272 | 1.9605 | 9.0786 | 17.3148 | |
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| 2.3992 | 2.0 | 544 | 1.8884 | 10.1443 | 17.3301 | |
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| 2.3992 | 3.0 | 816 | 1.8647 | 10.4816 | 17.3258 | |
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| 2.0832 | 4.0 | 1088 | 1.8473 | 10.7396 | 17.3231 | |
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| 2.0832 | 5.0 | 1360 | 1.8343 | 11.0937 | 17.2621 | |
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| 1.9193 | 6.0 | 1632 | 1.8282 | 11.1303 | 17.3098 | |
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| 1.9193 | 7.0 | 1904 | 1.8234 | 11.2971 | 17.2991 | |
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| 1.8351 | 8.0 | 2176 | 1.8241 | 11.3433 | 17.2621 | |
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| 1.8351 | 9.0 | 2448 | 1.8224 | 11.394 | 17.2691 | |
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| 1.7747 | 10.0 | 2720 | 1.8228 | 11.427 | 17.2674 | |
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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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