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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_CNN_NLP |
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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_CNN_NLP |
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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: 3.0479 |
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- Rouge1: 45.8751 |
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- Rouge2: 28.1917 |
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- Rougel: 42.0922 |
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- Rougelsum: 41.9934 |
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- Gen Len: 6433791.8333 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 500 |
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- num_epochs: 4 |
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- label_smoothing_factor: 0.1 |
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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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| 3.1748 | 0.4 | 40 | 3.1564 | 44.8208 | 26.6733 | 41.2873 | 41.226 | 6433791.8889 | |
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| 3.0649 | 0.8 | 80 | 2.9386 | 45.8469 | 27.8327 | 41.8543 | 41.8139 | 6433791.8556 | |
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| 2.6983 | 1.2 | 120 | 2.8712 | 47.7681 | 29.8568 | 43.9396 | 43.8816 | 6433791.8778 | |
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| 2.6725 | 1.6 | 160 | 2.8698 | 46.6433 | 29.2504 | 43.1299 | 43.0348 | 6433791.9333 | |
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| 2.7537 | 2.0 | 200 | 2.8534 | 47.0645 | 29.6233 | 43.5479 | 43.4841 | 6433791.8778 | |
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| 2.3728 | 2.4 | 240 | 2.9305 | 46.1673 | 28.848 | 42.6293 | 42.5577 | 6433791.8889 | |
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| 2.3572 | 2.8 | 280 | 2.9414 | 47.2408 | 29.4202 | 43.4668 | 43.3747 | 6433791.9 | |
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| 2.087 | 3.2 | 320 | 3.0366 | 46.652 | 28.7844 | 42.7646 | 42.6204 | 6433791.8778 | |
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| 2.1212 | 3.6 | 360 | 3.0169 | 46.6902 | 28.1997 | 42.5114 | 42.4226 | 6433791.8222 | |
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| 2.1264 | 4.0 | 400 | 3.0479 | 45.8751 | 28.1917 | 42.0922 | 41.9934 | 6433791.8333 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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