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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5_deed_sum_1 |
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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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# mt5_deed_sum_1 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co./google/mt5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5951 |
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- Rouge1: 0.0572 |
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- Rouge2: 0.0 |
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- Rougel: 0.0572 |
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- Rougelsum: 0.0572 |
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- Gen Len: 19.0 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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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- lr_scheduler_warmup_steps: 5000 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 24.1526 | 1.0 | 375 | 15.7524 | 0.7082 | 0.0 | 0.6842 | 0.6883 | 12.0881 | |
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| 11.2879 | 2.0 | 750 | 13.1581 | 0.7082 | 0.0 | 0.6842 | 0.6883 | 12.3208 | |
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| 10.5585 | 3.0 | 1125 | 7.4334 | 0.7082 | 0.0 | 0.6842 | 0.6883 | 17.1384 | |
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| 2.9668 | 4.0 | 1500 | 6.5357 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 3.7198 | 5.0 | 1875 | 2.1303 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 1.3383 | 6.0 | 2250 | 1.8675 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 3.4973 | 7.0 | 2625 | 1.6299 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 18.8994 | |
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| 11.7006 | 8.0 | 3000 | 4.6990 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 0.4529 | 9.0 | 3375 | 1.0729 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 1.2783 | 10.0 | 3750 | 0.9424 | 0.7487 | 0.0 | 0.7176 | 0.7257 | 19.0 | |
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| 0.7953 | 11.0 | 4125 | 0.8889 | 1.0108 | 0.2013 | 0.892 | 0.9014 | 19.0 | |
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| 0.9359 | 12.0 | 4500 | 0.7996 | 1.1489 | 0.3019 | 0.9952 | 0.9877 | 19.0 | |
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| 0.5759 | 13.0 | 4875 | 0.7622 | 0.1572 | 0.1144 | 0.1572 | 0.1572 | 19.0 | |
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| 0.1533 | 14.0 | 5250 | 0.7068 | 0.2144 | 0.1144 | 0.1715 | 0.1715 | 19.0 | |
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| 0.4524 | 15.0 | 5625 | 0.6760 | 0.3145 | 0.2287 | 0.3145 | 0.3145 | 19.0 | |
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| 1.0126 | 16.0 | 6000 | 0.6627 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
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| 0.1065 | 17.0 | 6375 | 0.6391 | 0.3145 | 0.2287 | 0.3145 | 0.3145 | 19.0 | |
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| 0.2096 | 18.0 | 6750 | 0.6419 | 0.2144 | 0.1144 | 0.2144 | 0.2144 | 19.0 | |
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| 0.5649 | 19.0 | 7125 | 0.6261 | 0.1572 | 0.1144 | 0.1572 | 0.1572 | 19.0 | |
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| 0.125 | 20.0 | 7500 | 0.6139 | 0.1572 | 0.1144 | 0.1572 | 0.1572 | 19.0 | |
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| 0.5511 | 21.0 | 7875 | 0.6057 | 0.3145 | 0.2287 | 0.3145 | 0.3145 | 19.0 | |
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| 0.0759 | 22.0 | 8250 | 0.6029 | 0.3145 | 0.2287 | 0.3145 | 0.3145 | 19.0 | |
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| 0.3491 | 23.0 | 8625 | 0.5995 | 0.3145 | 0.2287 | 0.3145 | 0.3145 | 19.0 | |
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| 0.3735 | 24.0 | 9000 | 0.5936 | 0.1572 | 0.1144 | 0.1572 | 0.1572 | 19.0 | |
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| 0.3451 | 25.0 | 9375 | 0.5951 | 0.0572 | 0.0 | 0.0572 | 0.0572 | 19.0 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0.dev20230811+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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