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--- |
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license: mit |
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library_name: transformers |
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base_model: nsi319/legal-led-base-16384 |
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model-index: |
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- name: results |
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results: [] |
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pipeline_tag: summarization |
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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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# results |
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This model is a fine-tuned version of [nsi319/legal-led-base-16384](https://huggingface.co/nsi319/legal-led-base-16384) on the joelniklaus/legal_case_document_summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7401 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.2 | 1.0 | 1924 | 2.8550 | |
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| 3.6193 | 2.0 | 3848 | 2.7593 | |
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| 2.7776 | 3.0 | 5772 | 2.7401 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
