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--- |
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license: mit |
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base_model: KingLTD/pretrain_Law_model_vit5_version2 |
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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: pretrain_Law_model_vit5_version3 |
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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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# pretrain_Law_model_vit5_version3 |
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This model is a fine-tuned version of [KingLTD/pretrain_Law_model_vit5_version2](https://huggingface.co/KingLTD/pretrain_Law_model_vit5_version2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1136 |
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- Rouge1: 0.4973 |
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- Rouge2: 0.4075 |
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- Rougel: 0.4532 |
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- Rougelsum: 0.4674 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| No log | 1.0 | 245 | 0.1060 | 0.4960 | 0.4069 | 0.4502 | 0.4664 | |
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| No log | 2.0 | 490 | 0.1070 | 0.4946 | 0.4053 | 0.4484 | 0.4644 | |
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| 0.146 | 3.0 | 735 | 0.1079 | 0.4908 | 0.3988 | 0.4456 | 0.4601 | |
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| 0.146 | 4.0 | 980 | 0.1107 | 0.4994 | 0.4094 | 0.4508 | 0.4665 | |
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| 0.1149 | 5.0 | 1225 | 0.1107 | 0.4944 | 0.4024 | 0.4483 | 0.4635 | |
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| 0.1149 | 6.0 | 1470 | 0.1126 | 0.4931 | 0.4028 | 0.4478 | 0.4626 | |
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| 0.0956 | 7.0 | 1715 | 0.1124 | 0.4991 | 0.4108 | 0.4556 | 0.4701 | |
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| 0.0956 | 8.0 | 1960 | 0.1122 | 0.4944 | 0.4082 | 0.4515 | 0.4655 | |
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| 0.0822 | 9.0 | 2205 | 0.1133 | 0.4996 | 0.4111 | 0.4557 | 0.4699 | |
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| 0.0822 | 10.0 | 2450 | 0.1136 | 0.4973 | 0.4075 | 0.4532 | 0.4674 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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