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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: flan-t5-base-extraction-cnndm_2000-all-hint_precision-ep50 |
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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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# flan-t5-base-extraction-cnndm_2000-all-hint_precision-ep50 |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8409 |
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- Hint Hit Num: 2.3443 |
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- Hint Precision: 0.4272 |
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- Num: 5.472 |
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- Gen Len: 18.9975 |
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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: 60 |
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- eval_batch_size: 400 |
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- seed: 1799 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Hint Hit Num | Hint Precision | Num | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:| |
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| 2.2521 | 5.88 | 200 | 1.8616 | 2.2495 | 0.4197 | 5.3613 | 18.9832 | |
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| 1.9538 | 11.76 | 400 | 1.8307 | 2.2661 | 0.4202 | 5.3879 | 18.996 | |
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| 1.8538 | 17.65 | 600 | 1.8238 | 2.3191 | 0.4251 | 5.446 | 18.9979 | |
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| 1.7799 | 23.53 | 800 | 1.8277 | 2.3338 | 0.4259 | 5.4634 | 18.9975 | |
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| 1.7242 | 29.41 | 1000 | 1.8360 | 2.3131 | 0.4243 | 5.4378 | 18.9982 | |
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| 1.6819 | 35.29 | 1200 | 1.8409 | 2.3443 | 0.4272 | 5.472 | 18.9975 | |
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| 1.6535 | 41.18 | 1400 | 1.8451 | 2.3363 | 0.4257 | 5.4672 | 18.9976 | |
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| 1.6397 | 47.06 | 1600 | 1.8472 | 2.3414 | 0.4257 | 5.4776 | 18.9982 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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