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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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- opus_infopankki |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-tr-en-finetuned-tr-to-en |
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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: opus_infopankki |
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type: opus_infopankki |
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args: en-tr |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 54.7617 |
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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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# opus-mt-tr-en-finetuned-tr-to-en |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tr-en](https://huggingface.co/Helsinki-NLP/opus-mt-tr-en) on the opus_infopankki dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6924 |
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- Bleu: 54.7617 |
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- Gen Len: 13.5501 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 16 |
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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 | 412 | 1.1776 | 43.3104 | 12.9297 | |
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| 1.4032 | 2.0 | 824 | 1.0750 | 45.7912 | 12.9155 | |
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| 1.2268 | 3.0 | 1236 | 1.0019 | 47.6255 | 12.9251 | |
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| 1.141 | 4.0 | 1648 | 0.9411 | 49.0649 | 12.9302 | |
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| 1.0651 | 5.0 | 2060 | 0.8929 | 50.4894 | 12.9066 | |
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| 1.0651 | 6.0 | 2472 | 0.8519 | 51.5072 | 12.9067 | |
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| 1.0025 | 7.0 | 2884 | 0.8180 | 52.5035 | 12.8875 | |
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| 0.9582 | 8.0 | 3296 | 0.7893 | 51.7587 | 13.5338 | |
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| 0.9173 | 9.0 | 3708 | 0.7655 | 52.3566 | 13.5376 | |
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| 0.8892 | 10.0 | 4120 | 0.7449 | 53.0488 | 13.5545 | |
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| 0.8639 | 11.0 | 4532 | 0.7285 | 53.5965 | 13.5539 | |
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| 0.8639 | 12.0 | 4944 | 0.7152 | 53.9433 | 13.5547 | |
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| 0.8424 | 13.0 | 5356 | 0.7053 | 54.2509 | 13.5502 | |
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| 0.8317 | 14.0 | 5768 | 0.6981 | 54.5339 | 13.5502 | |
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| 0.817 | 15.0 | 6180 | 0.6938 | 54.7068 | 13.5448 | |
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| 0.8155 | 16.0 | 6592 | 0.6924 | 54.7617 | 13.5501 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.7.1+cu110 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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