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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: Super_legal_text_summarizer |
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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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# Super_legal_text_summarizer |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8242 |
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- Rouge1: 0.4168 |
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- Rouge2: 0.1843 |
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- Rougel: 0.26 |
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- Rougelsum: 0.2614 |
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- Gen Len: 126.1232 |
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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-06 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 12 |
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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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- 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 | 0.9889 | 67 | 2.0691 | 0.3965 | 0.1608 | 0.2317 | 0.2325 | 134.8522 | |
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| No log | 1.9926 | 135 | 1.9581 | 0.4184 | 0.1826 | 0.2539 | 0.255 | 133.4433 | |
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| No log | 2.9963 | 203 | 1.9041 | 0.4129 | 0.1792 | 0.2554 | 0.2563 | 127.0591 | |
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| No log | 4.0 | 271 | 1.8745 | 0.4111 | 0.1769 | 0.2579 | 0.2586 | 126.7635 | |
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| No log | 4.9889 | 338 | 1.8539 | 0.4122 | 0.1754 | 0.258 | 0.2586 | 126.0542 | |
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| No log | 5.9926 | 406 | 1.8414 | 0.4197 | 0.1806 | 0.2603 | 0.2613 | 130.8177 | |
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| No log | 6.9963 | 474 | 1.8334 | 0.4058 | 0.1712 | 0.2532 | 0.2539 | 126.1281 | |
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| 1.9669 | 8.0 | 542 | 1.8284 | 0.4129 | 0.1818 | 0.2587 | 0.2596 | 125.798 | |
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| 1.9669 | 8.9889 | 609 | 1.8246 | 0.4129 | 0.1802 | 0.257 | 0.2582 | 126.6158 | |
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| 1.9669 | 9.8893 | 670 | 1.8242 | 0.4168 | 0.1843 | 0.26 | 0.2614 | 126.1232 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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