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--- |
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license: bsd-3-clause |
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base_model: pszemraj/led-base-book-summary |
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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: device |
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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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# device |
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This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0247 |
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- Rouge1: 0.6269 |
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- Rouge2: 0.3921 |
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- Rougel: 0.5261 |
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- Rougelsum: 0.5266 |
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- Gen Len: 67.5584 |
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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: 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: 8 |
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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 | 274 | 1.0933 | 0.5918 | 0.3356 | 0.4785 | 0.4788 | 72.0547 | |
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| 1.1731 | 2.0 | 548 | 1.0177 | 0.5985 | 0.3525 | 0.4902 | 0.4906 | 68.5055 | |
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| 1.1731 | 3.0 | 822 | 0.9976 | 0.6063 | 0.3603 | 0.4982 | 0.4982 | 69.7263 | |
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| 0.7216 | 4.0 | 1096 | 0.9922 | 0.6113 | 0.3735 | 0.5081 | 0.5084 | 68.1861 | |
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| 0.7216 | 5.0 | 1370 | 0.9957 | 0.6193 | 0.3826 | 0.5216 | 0.5217 | 65.4617 | |
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| 0.5252 | 6.0 | 1644 | 1.0127 | 0.6252 | 0.3877 | 0.5231 | 0.5236 | 68.0584 | |
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| 0.5252 | 7.0 | 1918 | 1.0221 | 0.6252 | 0.3897 | 0.5246 | 0.5246 | 67.5931 | |
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| 0.4079 | 8.0 | 2192 | 1.0247 | 0.6269 | 0.3921 | 0.5261 | 0.5266 | 67.5584 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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