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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- data |
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metrics: |
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- bleu |
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model-index: |
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- name: mbart-en-id-smaller-indo-amr-generation-translated-nafkhan |
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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: data |
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type: data |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 50.4231 |
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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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# mbart-en-id-smaller-indo-amr-generation-translated-nafkhan |
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This model was trained from scratch on the data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9816 |
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- Bleu: 50.4231 |
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- Gen Len: 8.2667 |
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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: 1e-06 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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- seed: 42 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 25 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 640.0 |
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- label_smoothing_factor: 0.1 |
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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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| 1.5364 | 39.7351 | 3600 | 2.0474 | 41.1359 | 9.5667 | |
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| 1.4794 | 79.4702 | 7200 | 2.0256 | 44.4125 | 9.0667 | |
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| 1.3621 | 119.2053 | 10800 | 2.0037 | 49.121 | 8.8 | |
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| 1.3278 | 158.9404 | 14400 | 1.9857 | 52.1498 | 8.5 | |
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| 1.2906 | 198.6755 | 18000 | 2.0048 | 48.3044 | 8.5333 | |
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| 1.2272 | 238.4106 | 21600 | 2.0017 | 47.3367 | 8.6 | |
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| 1.2339 | 278.1457 | 25200 | 1.9705 | 46.5655 | 8.5667 | |
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| 1.194 | 317.8808 | 28800 | 1.9818 | 51.4066 | 8.5 | |
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| 1.1416 | 357.6159 | 32400 | 1.9699 | 45.7022 | 8.4333 | |
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| 1.1437 | 397.3510 | 36000 | 1.9692 | 46.8726 | 8.2 | |
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| 1.156 | 437.0861 | 39600 | 1.9549 | 48.7386 | 8.4333 | |
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| 1.1355 | 476.8212 | 43200 | 1.9726 | 48.3929 | 8.5667 | |
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| 1.1246 | 516.5563 | 46800 | 1.9701 | 47.8897 | 8.4667 | |
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| 1.1132 | 556.2914 | 50400 | 1.9736 | 48.9071 | 8.3667 | |
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| 1.0843 | 596.0265 | 54000 | 1.9765 | 49.9897 | 8.4333 | |
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| 1.1211 | 635.7616 | 57600 | 1.9816 | 50.4231 | 8.2667 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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