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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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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_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: 8.7934 |
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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_wmt14_En_Fr_1million |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co./google-t5/t5-small) on the wmt14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3618 |
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- Bleu: 8.7934 |
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- Gen Len: 17.9953 |
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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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| 1.0796 | 1.0 | 1667 | 1.1872 | 9.2959 | 18.0253 | |
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| 1.01 | 2.0 | 3334 | 1.2029 | 9.1594 | 18.0187 | |
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| 0.9686 | 3.0 | 5001 | 1.2114 | 9.2836 | 18.0123 | |
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| 0.9366 | 4.0 | 6668 | 1.2261 | 9.18 | 17.995 | |
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| 0.8999 | 5.0 | 8335 | 1.2319 | 9.2754 | 17.9793 | |
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| 0.8769 | 6.0 | 10002 | 1.2413 | 9.1705 | 18.026 | |
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| 0.8536 | 7.0 | 11669 | 1.2502 | 9.036 | 17.9987 | |
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| 0.8273 | 8.0 | 13336 | 1.2633 | 9.2003 | 18.006 | |
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| 0.8125 | 9.0 | 15003 | 1.2740 | 9.0991 | 18.009 | |
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| 0.7905 | 10.0 | 16670 | 1.2835 | 8.9005 | 18.007 | |
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| 0.774 | 11.0 | 18337 | 1.2943 | 9.0676 | 17.9967 | |
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| 0.76 | 12.0 | 20004 | 1.3023 | 9.0644 | 18.0227 | |
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| 0.7358 | 13.0 | 21671 | 1.3125 | 8.9858 | 18.0027 | |
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| 0.7238 | 14.0 | 23338 | 1.3204 | 9.0178 | 18.0073 | |
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| 0.7143 | 15.0 | 25005 | 1.3317 | 8.9826 | 18.015 | |
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| 0.6988 | 16.0 | 26672 | 1.3402 | 8.9224 | 18.0073 | |
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| 0.6829 | 17.0 | 28339 | 1.3500 | 8.9307 | 17.996 | |
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| 0.6776 | 18.0 | 30006 | 1.3517 | 8.8798 | 17.9987 | |
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| 0.6695 | 19.0 | 31673 | 1.3585 | 8.895 | 17.9967 | |
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| 0.6637 | 20.0 | 33340 | 1.3618 | 8.7934 | 17.9953 | |
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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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