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--- |
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base_model: X-Wang/pruned-mt5-small |
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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: pruned-mt5-small |
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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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# pruned-mt5-small |
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This model is a fine-tuned version of [X-Wang/pruned-mt5-small](https://huggingface.co/X-Wang/pruned-mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4431 |
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- Bleu: 11.4084 |
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- Gen Len: 16.1053 |
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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: 0.0005 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 24 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 2 |
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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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| 3.3446 | 0.07 | 2000 | 2.9103 | 10.3957 | 16.0567 | |
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| 2.8425 | 0.14 | 4000 | 2.8570 | 10.5695 | 16.1895 | |
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| 3.186 | 0.21 | 6000 | 2.8137 | 10.5958 | 16.1523 | |
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| 2.788 | 0.28 | 8000 | 2.7593 | 10.7553 | 16.0138 | |
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| 2.9075 | 0.35 | 10000 | 2.7266 | 10.9199 | 16.2016 | |
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| 3.0579 | 0.42 | 12000 | 2.7030 | 10.6 | 16.0496 | |
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| 2.3618 | 0.49 | 14000 | 2.6547 | 10.8026 | 16.0412 | |
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| 3.079 | 0.56 | 16000 | 2.6441 | 10.7945 | 16.1148 | |
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| 2.7597 | 0.63 | 18000 | 2.6244 | 10.5877 | 16.0507 | |
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| 2.8533 | 0.7 | 20000 | 2.6049 | 10.9986 | 16.1145 | |
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| 2.843 | 0.77 | 22000 | 2.5836 | 10.9173 | 16.0826 | |
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| 2.8268 | 0.84 | 24000 | 2.5685 | 10.8136 | 16.0516 | |
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| 2.7021 | 0.91 | 26000 | 2.5509 | 11.326 | 16.0554 | |
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| 3.338 | 0.98 | 28000 | 2.5289 | 11.1485 | 16.0333 | |
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| 2.7374 | 1.05 | 30000 | 2.5220 | 11.0166 | 16.0998 | |
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| 2.7996 | 1.12 | 32000 | 2.5077 | 11.1316 | 16.131 | |
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| 2.6897 | 1.19 | 34000 | 2.4994 | 11.0811 | 16.1139 | |
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| 2.4107 | 1.26 | 36000 | 2.4877 | 11.2641 | 16.142 | |
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| 2.7695 | 1.33 | 38000 | 2.4756 | 11.2135 | 16.0977 | |
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| 3.3271 | 1.41 | 40000 | 2.4658 | 11.3328 | 16.0953 | |
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| 2.2641 | 1.48 | 42000 | 2.4612 | 11.3065 | 16.0549 | |
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| 2.6594 | 1.55 | 44000 | 2.4556 | 11.2684 | 16.1371 | |
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| 2.7322 | 1.62 | 46000 | 2.4520 | 11.3739 | 16.1058 | |
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| 2.6824 | 1.69 | 48000 | 2.4462 | 11.3335 | 16.1043 | |
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| 2.3369 | 1.76 | 50000 | 2.4455 | 11.3851 | 16.1239 | |
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| 2.9537 | 1.83 | 52000 | 2.4430 | 11.4026 | 16.0858 | |
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| 2.3928 | 1.9 | 54000 | 2.4433 | 11.301 | 16.1129 | |
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| 2.4714 | 1.97 | 56000 | 2.4431 | 11.4084 | 16.1053 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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