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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- accuracy |
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model-index: |
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- name: mt5-base-translation-spa-pbb |
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results: [] |
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datasets: |
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- Broomva/translation_pbb_spa |
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language: |
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- es |
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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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# mt5-base-translation-spa-pbb |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0646 |
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- Bleu: 0.5194 |
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- Gen Len: 5.3808 |
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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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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 30 |
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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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| 9.0597 | 1.0 | 304 | 7.8135 | 0.0148 | 4.6469 | |
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| 6.2294 | 2.0 | 608 | 4.9617 | 0.0 | 3.9209 | |
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| 4.8326 | 3.0 | 912 | 4.0494 | 0.0 | 4.3808 | |
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| 4.582 | 4.0 | 1216 | 3.7069 | 0.0 | 5.3979 | |
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| 5.4762 | 5.0 | 1520 | 3.5463 | 0.0 | 5.6759 | |
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| 4.3875 | 6.0 | 1824 | 3.4731 | 0.0 | 5.6258 | |
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| 4.2873 | 7.0 | 2128 | 3.3832 | 0.0 | 5.5455 | |
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| 4.1326 | 8.0 | 2432 | 3.3424 | 0.0 | 5.4756 | |
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| 3.5728 | 9.0 | 2736 | 3.2956 | 0.0 | 5.1792 | |
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| 3.1873 | 10.0 | 3040 | 3.2690 | 0.0 | 5.5903 | |
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| 2.9436 | 11.0 | 3344 | 3.2465 | 0.1237 | 5.7655 | |
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| 4.2955 | 12.0 | 3648 | 3.2054 | 0.1741 | 5.4466 | |
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| 3.8722 | 13.0 | 3952 | 3.1764 | 0.1887 | 5.2161 | |
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| 3.5391 | 14.0 | 4256 | 3.1688 | 0.0951 | 5.7312 | |
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| 3.8012 | 15.0 | 4560 | 3.1480 | 0.1948 | 5.2964 | |
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| 3.1148 | 16.0 | 4864 | 3.1401 | 0.2397 | 5.7589 | |
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| 3.2699 | 17.0 | 5168 | 3.1186 | 0.33 | 5.386 | |
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| 4.3355 | 18.0 | 5472 | 3.1092 | 0.4637 | 5.1383 | |
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| 3.5792 | 19.0 | 5776 | 3.0966 | 0.3286 | 5.4374 | |
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| 3.1429 | 20.0 | 6080 | 3.0923 | 0.418 | 5.2964 | |
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| 3.4155 | 21.0 | 6384 | 3.0900 | 0.3938 | 5.4848 | |
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| 3.4515 | 22.0 | 6688 | 3.0755 | 0.4062 | 5.4124 | |
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| 2.8244 | 23.0 | 6992 | 3.0717 | 0.4218 | 5.3663 | |
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| 2.9253 | 24.0 | 7296 | 3.0663 | 0.3633 | 5.5692 | |
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| 2.1757 | 25.0 | 7600 | 3.0640 | 0.4768 | 5.4282 | |
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| 2.9356 | 26.0 | 7904 | 3.0646 | 0.5194 | 5.3808 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
