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--- |
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license: mit |
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base_model: facebook/bart-large-cnn |
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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: bart-large-cnn-with-generate-finetune-indosum |
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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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# bart-large-cnn-with-generate-finetune-indosum |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0686 |
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- Rouge1: 0.8873 |
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- Rouge2: 0.8491 |
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- Rougel: 0.8815 |
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- Rougelsum: 0.8815 |
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- Gen Len: 128.9129 |
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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: 16 |
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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: 10 |
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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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| 0.2591 | 1.0 | 4460 | 0.2573 | 0.7218 | 0.6324 | 0.6969 | 0.6967 | 129.0612 | |
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| 0.1657 | 2.0 | 8920 | 0.1600 | 0.7613 | 0.6815 | 0.7401 | 0.7401 | 128.9508 | |
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| 0.0945 | 3.0 | 13380 | 0.1157 | 0.8001 | 0.7311 | 0.7837 | 0.7835 | 128.9105 | |
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| 0.0508 | 4.0 | 17840 | 0.0976 | 0.8277 | 0.7704 | 0.8152 | 0.8152 | 129.0289 | |
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| 0.0296 | 5.0 | 22300 | 0.0853 | 0.857 | 0.8087 | 0.8473 | 0.8471 | 128.9257 | |
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| 0.0176 | 6.0 | 26760 | 0.0793 | 0.8702 | 0.8279 | 0.8632 | 0.8633 | 128.9113 | |
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| 0.0112 | 7.0 | 31220 | 0.0605 | 0.8789 | 0.8377 | 0.872 | 0.8721 | 128.8637 | |
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| 0.0074 | 8.0 | 35680 | 0.0597 | 0.88 | 0.84 | 0.8731 | 0.8732 | 128.9305 | |
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| 0.005 | 9.0 | 40140 | 0.0658 | 0.8822 | 0.8433 | 0.8761 | 0.8761 | 128.949 | |
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| 0.0036 | 10.0 | 44600 | 0.0686 | 0.8873 | 0.8491 | 0.8815 | 0.8815 | 128.9129 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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