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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-fp16 |
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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: 9.2226 |
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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-fp16 |
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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: 1.9416 |
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- Bleu: 9.2226 |
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- Gen Len: 17.3311 |
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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: 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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- 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 | 272 | 2.1671 | 3.8489 | 17.6382 | |
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| 2.6715 | 2.0 | 544 | 2.0660 | 6.4354 | 17.4905 | |
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| 2.6715 | 3.0 | 816 | 2.0206 | 7.4092 | 17.3708 | |
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| 2.4325 | 4.0 | 1088 | 1.9926 | 8.1453 | 17.3685 | |
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| 2.4325 | 5.0 | 1360 | 1.9739 | 8.6739 | 17.3521 | |
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| 2.3312 | 6.0 | 1632 | 1.9602 | 8.8808 | 17.3681 | |
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| 2.3312 | 7.0 | 1904 | 1.9509 | 9.1173 | 17.3491 | |
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| 2.2946 | 8.0 | 2176 | 1.9465 | 9.1504 | 17.3414 | |
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| 2.2946 | 9.0 | 2448 | 1.9426 | 9.2372 | 17.3398 | |
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| 2.2665 | 10.0 | 2720 | 1.9416 | 9.2226 | 17.3311 | |
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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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