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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wmt14 |
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metrics: |
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- bleu |
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model-index: |
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- name: T5_base_wmt14_En_Fr_1million |
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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: wmt14 |
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type: wmt14 |
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config: fr-en |
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split: validation |
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args: fr-en |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 8.5002 |
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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_wmt14_En_Fr_1million |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the wmt14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9945 |
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- Bleu: 8.5002 |
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- Gen Len: 18.0143 |
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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: 0.001 |
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- train_batch_size: 60 |
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- eval_batch_size: 60 |
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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: 20 |
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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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| 0.9735 | 1.0 | 1667 | 1.1059 | 9.3433 | 17.994 | |
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| 0.8671 | 2.0 | 3334 | 1.1192 | 9.3551 | 18.008 | |
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| 0.7975 | 3.0 | 5001 | 1.1509 | 9.4297 | 17.996 | |
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| 0.737 | 4.0 | 6668 | 1.1819 | 9.0739 | 18.0223 | |
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| 0.6746 | 5.0 | 8335 | 1.2076 | 9.1258 | 17.9873 | |
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| 0.6314 | 6.0 | 10002 | 1.2640 | 9.1364 | 18.0207 | |
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| 0.5833 | 7.0 | 11669 | 1.2948 | 8.8072 | 17.9907 | |
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| 0.5349 | 8.0 | 13336 | 1.3525 | 8.8513 | 17.9867 | |
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| 0.5025 | 9.0 | 15003 | 1.4087 | 8.7599 | 18.0027 | |
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| 0.4614 | 10.0 | 16670 | 1.4562 | 8.6011 | 18.015 | |
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| 0.4227 | 11.0 | 18337 | 1.5169 | 8.6315 | 18.018 | |
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| 0.3938 | 12.0 | 20004 | 1.5842 | 8.6045 | 18.0133 | |
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| 0.358 | 13.0 | 21671 | 1.6334 | 8.459 | 17.9997 | |
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| 0.3271 | 14.0 | 23338 | 1.6989 | 8.4979 | 17.9937 | |
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| 0.3056 | 15.0 | 25005 | 1.7529 | 8.5421 | 18.0357 | |
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| 0.278 | 16.0 | 26672 | 1.8151 | 8.3963 | 18.0027 | |
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| 0.2548 | 17.0 | 28339 | 1.8812 | 8.3497 | 18.0193 | |
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| 0.238 | 18.0 | 30006 | 1.9249 | 8.4306 | 18.0227 | |
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| 0.223 | 19.0 | 31673 | 1.9742 | 8.5156 | 18.013 | |
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| 0.2112 | 20.0 | 33340 | 1.9945 | 8.5002 | 18.0143 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.2 |
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