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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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model-index: |
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- name: EN_mt5-base_15_spider |
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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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# EN_mt5-base_15_spider |
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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: 0.3557 |
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- Rouge2 Precision: 0.6104 |
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- Rouge2 Recall: 0.4164 |
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- Rouge2 Fmeasure: 0.4669 |
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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: 5e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 16 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 9.1945 | 1.0 | 722 | 1.9988 | 0.2524 | 0.1722 | 0.1809 | |
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| 2.7281 | 2.0 | 1444 | 0.3721 | 0.4727 | 0.3003 | 0.3376 | |
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| 0.2067 | 3.0 | 2166 | 0.3160 | 0.5435 | 0.3541 | 0.4033 | |
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| 0.1692 | 4.0 | 2888 | 0.3153 | 0.5628 | 0.3863 | 0.4314 | |
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| 0.1252 | 5.0 | 3610 | 0.3225 | 0.5764 | 0.3907 | 0.4381 | |
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| 0.1117 | 6.0 | 4332 | 0.3165 | 0.5707 | 0.3891 | 0.435 | |
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| 0.0973 | 7.0 | 5054 | 0.3269 | 0.5693 | 0.3868 | 0.4335 | |
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| 0.0897 | 8.0 | 5776 | 0.3365 | 0.585 | 0.4009 | 0.4478 | |
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| 0.082 | 9.0 | 6498 | 0.3407 | 0.6035 | 0.4129 | 0.4619 | |
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| 0.0721 | 10.0 | 7220 | 0.3453 | 0.5963 | 0.4089 | 0.4568 | |
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| 0.0703 | 11.0 | 7942 | 0.3434 | 0.6032 | 0.4137 | 0.4629 | |
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| 0.0638 | 12.0 | 8664 | 0.3505 | 0.6077 | 0.4178 | 0.4667 | |
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| 0.0615 | 13.0 | 9386 | 0.3509 | 0.611 | 0.4169 | 0.467 | |
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| 0.0599 | 14.0 | 10108 | 0.3554 | 0.608 | 0.4153 | 0.4651 | |
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| 0.058 | 15.0 | 10830 | 0.3557 | 0.6104 | 0.4164 | 0.4669 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.7.dev0 |
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- Tokenizers 0.13.3 |
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