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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ALL_mt5-base_15_spider_no_sch_15_wikiSQL_no_sch_128 |
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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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# ALL_mt5-base_15_spider_no_sch_15_wikiSQL_no_sch_128 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0225 |
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- Rouge2 Precision: 0.8419 |
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- Rouge2 Recall: 0.5664 |
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- Rouge2 Fmeasure: 0.6439 |
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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: 15 |
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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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| 0.2971 | 1.0 | 1293 | 0.1770 | 0.5043 | 0.3352 | 0.3788 | |
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| 0.1766 | 2.0 | 2586 | 0.1177 | 0.5844 | 0.3896 | 0.4412 | |
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| 0.1416 | 3.0 | 3879 | 0.0899 | 0.6329 | 0.4197 | 0.4773 | |
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| 0.1108 | 4.0 | 5172 | 0.0700 | 0.6794 | 0.4555 | 0.5171 | |
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| 0.0962 | 5.0 | 6465 | 0.0562 | 0.7204 | 0.4823 | 0.5478 | |
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| 0.0814 | 6.0 | 7758 | 0.0473 | 0.7503 | 0.5072 | 0.5746 | |
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| 0.0709 | 7.0 | 9051 | 0.0405 | 0.7655 | 0.5153 | 0.5845 | |
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| 0.0651 | 8.0 | 10344 | 0.0358 | 0.7863 | 0.5298 | 0.601 | |
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| 0.0589 | 9.0 | 11637 | 0.0312 | 0.7996 | 0.538 | 0.6108 | |
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| 0.0553 | 10.0 | 12930 | 0.0288 | 0.8123 | 0.5482 | 0.6218 | |
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| 0.0515 | 11.0 | 14223 | 0.0262 | 0.8229 | 0.553 | 0.6283 | |
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| 0.0487 | 12.0 | 15516 | 0.0246 | 0.8247 | 0.555 | 0.6304 | |
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| 0.0466 | 13.0 | 16809 | 0.0236 | 0.835 | 0.5611 | 0.6377 | |
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| 0.0445 | 14.0 | 18102 | 0.0227 | 0.8414 | 0.5662 | 0.6435 | |
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| 0.044 | 15.0 | 19395 | 0.0225 | 0.8419 | 0.5664 | 0.6439 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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