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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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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-base-ckb |
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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-base-ckb |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6353 |
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- Rouge1: 0.0 |
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- Rouge2: 0.0 |
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- Rougel: 0.0 |
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- Rougelsum: 0.0 |
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- Cer: 4.7349 |
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- Gen Len: 13.2035 |
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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: 320 |
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- eval_batch_size: 256 |
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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: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 3.5765 | 0.11 | 500 | 10.3648 | 16.358 | 3.4338 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 3.1749 | 0.22 | 1000 | 10.955 | 15.828 | 3.0110 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.8696 | 0.33 | 1500 | 11.2579 | 15.358 | 2.6943 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.6279 | 0.43 | 2000 | 11.6734 | 14.8565 | 2.4300 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4166 | 0.54 | 2500 | 11.028 | 14.523 | 2.2248 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.2444 | 0.65 | 3000 | 10.4379 | 14.4185 | 2.0490 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.0902 | 0.76 | 3500 | 10.0905 | 14.242 | 1.8756 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.9565 | 0.87 | 4000 | 9.7629 | 14.042 | 1.7377 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.8319 | 0.98 | 4500 | 9.4737 | 13.877 | 1.6244 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.7104 | 1.09 | 5000 | 9.153 | 13.825 | 1.5353 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.6148 | 1.2 | 5500 | 8.8125 | 13.726 | 1.4422 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.5459 | 1.3 | 6000 | 8.5589 | 13.681 | 1.3755 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.4837 | 1.41 | 6500 | 8.2717 | 13.6225 | 1.3035 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.4219 | 1.52 | 7000 | 8.0684 | 13.549 | 1.2407 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.3743 | 1.63 | 7500 | 7.7684 | 13.502 | 1.1865 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.3318 | 1.74 | 8000 | 7.5247 | 13.509 | 1.1503 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.2893 | 1.85 | 8500 | 7.3826 | 13.456 | 1.1085 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 1.2228 | 2.0 | 9198 | 1.0506 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0411 | 13.3935 | |
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| 0.9343 | 3.0 | 13797 | 0.7769 | 0.0 | 0.0 | 0.0 | 0.0 | 5.5303 | 13.2935 | |
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| 0.7915 | 4.0 | 18396 | 0.6663 | 0.0 | 0.0 | 0.0 | 0.0 | 4.8928 | 13.209 | |
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| 0.7436 | 5.0 | 22995 | 0.6353 | 0.0 | 0.0 | 0.0 | 0.0 | 4.7349 | 13.2035 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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