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--- |
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license: mit |
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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-science-v3-e1-v4-e6-manual |
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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-science-v3-e1-v4-e6-manual |
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This model is a fine-tuned version of [theojolliffe/bart-cnn-science-v3-e1](https://huggingface.co/theojolliffe/bart-cnn-science-v3-e1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4513 |
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- Rouge1: 51.4471 |
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- Rouge2: 31.5595 |
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- Rougel: 31.7717 |
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- Rougelsum: 49.4999 |
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- Gen Len: 142.0 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 6 |
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- mixed_precision_training: Native AMP |
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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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| No log | 1.0 | 42 | 1.0691 | 51.1883 | 31.2479 | 33.7004 | 48.9571 | 142.0 | |
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| No log | 2.0 | 84 | 1.0883 | 51.7634 | 29.8573 | 30.7155 | 49.3378 | 142.0 | |
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| No log | 3.0 | 126 | 1.2355 | 52.9606 | 31.3539 | 33.5131 | 49.9275 | 142.0 | |
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| No log | 4.0 | 168 | 1.3430 | 52.2108 | 32.7896 | 34.65 | 50.4271 | 139.1 | |
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| No log | 5.0 | 210 | 1.3963 | 51.5335 | 30.4157 | 31.5759 | 49.6904 | 142.0 | |
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| No log | 6.0 | 252 | 1.4513 | 51.4471 | 31.5595 | 31.7717 | 49.4999 | 142.0 | |
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### Framework versions |
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- Transformers 4.20.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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