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--- |
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base_model: microsoft/prophetnet-large-uncased |
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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: prophetnet-large-uncased-samsum |
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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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# prophetnet-large-uncased-samsum |
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This model is a fine-tuned version of [microsoft/prophetnet-large-uncased](https://huggingface.co/microsoft/prophetnet-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8806 |
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- Rouge1: 42.7998 |
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- Rouge2: 20.6028 |
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- Rougel: 32.7447 |
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- Rougelsum: 38.6683 |
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- Gen Len: 46.5763 |
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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: 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: 5 |
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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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| 2.2102 | 1.0 | 1842 | 1.9800 | 46.2865 | 22.7077 | 36.6175 | 42.7446 | 37.8791 | |
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| 1.6648 | 2.0 | 3684 | 1.8943 | 43.8689 | 21.5646 | 34.0359 | 39.9618 | 44.8193 | |
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| 1.2354 | 3.0 | 5526 | 1.8806 | 42.7998 | 20.6028 | 32.7447 | 38.6683 | 46.5763 | |
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| 0.9176 | 4.0 | 7368 | 1.9474 | 43.5931 | 20.9008 | 33.236 | 39.1182 | 46.1087 | |
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| 0.6827 | 5.0 | 9210 | 2.0220 | 42.9591 | 20.2499 | 32.94 | 38.5586 | 46.9658 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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