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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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metrics: |
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- bleu |
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model-index: |
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- name: bart-base-en-to-de |
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results: [] |
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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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# bart-base-en-to-de |
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This model is a fine-tuned version of [ahazeemi/bart-base-finetuned-en-to-de](https://huggingface.co/ahazeemi/bart-base-finetuned-en-to-de) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9665 |
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- Bleu: 4.7851 |
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- Gen Len: 19.453 |
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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: 3e-05 |
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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: 1 |
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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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| 1.319 | 0.04 | 5000 | 1.1247 | 4.4467 | 19.447 | |
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| 1.295 | 0.07 | 10000 | 1.1012 | 4.4235 | 19.458 | |
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| 1.2901 | 0.11 | 15000 | 1.0923 | 4.4386 | 19.4423 | |
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| 1.2678 | 0.14 | 20000 | 1.0803 | 4.5259 | 19.4557 | |
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| 1.267 | 0.18 | 25000 | 1.0724 | 4.5534 | 19.4653 | |
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| 1.2444 | 0.21 | 30000 | 1.0591 | 4.4944 | 19.4623 | |
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| 1.2365 | 0.25 | 35000 | 1.0509 | 4.5736 | 19.446 | |
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| 1.2137 | 0.28 | 40000 | 1.0400 | 4.5346 | 19.4553 | |
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| 1.214 | 0.32 | 45000 | 1.0340 | 4.5733 | 19.4543 | |
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| 1.218 | 0.35 | 50000 | 1.0283 | 4.6076 | 19.4693 | |
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| 1.2118 | 0.39 | 55000 | 1.0225 | 4.6192 | 19.454 | |
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| 1.1948 | 0.43 | 60000 | 1.0152 | 4.6082 | 19.4553 | |
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| 1.1932 | 0.46 | 65000 | 1.0128 | 4.665 | 19.449 | |
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| 1.1889 | 0.5 | 70000 | 1.0028 | 4.6929 | 19.4493 | |
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| 1.2154 | 0.53 | 75000 | 1.0004 | 4.7151 | 19.4477 | |
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| 1.194 | 0.57 | 80000 | 0.9950 | 4.6655 | 19.467 | |
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| 1.1847 | 0.6 | 85000 | 0.9966 | 4.708 | 19.451 | |
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| 1.1848 | 0.64 | 90000 | 0.9897 | 4.7794 | 19.458 | |
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| 1.1762 | 0.67 | 95000 | 0.9866 | 4.7204 | 19.4523 | |
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| 1.1818 | 0.71 | 100000 | 0.9803 | 4.7137 | 19.458 | |
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| 1.1613 | 0.75 | 105000 | 0.9788 | 4.7652 | 19.4573 | |
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| 1.1738 | 0.78 | 110000 | 0.9775 | 4.8088 | 19.453 | |
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| 1.1569 | 0.82 | 115000 | 0.9752 | 4.7522 | 19.4577 | |
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| 1.1631 | 0.85 | 120000 | 0.9713 | 4.7301 | 19.4513 | |
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| 1.1517 | 0.89 | 125000 | 0.9690 | 4.7935 | 19.456 | |
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| 1.1577 | 0.92 | 130000 | 0.9686 | 4.791 | 19.4543 | |
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| 1.1607 | 0.96 | 135000 | 0.9676 | 4.7529 | 19.4533 | |
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| 1.153 | 0.99 | 140000 | 0.9665 | 4.7851 | 19.453 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.0+cu116 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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