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Final_Fine_Tuned_Legal_Led
Feluda/Final_Fine_Tuned_Legal_Led
Final_Fine_Tuned_Legal_Led is a summarization model from Feluda. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- License
- mit
- Model type
- led
- Access
- Public
- Created
- Dec 27, 2023
- Updated
- Jan 11, 2024
- SHA
- edbf49cf
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
results
This model is a fine-tuned version of nsi319/legal-led-base-16384 on the joelniklaus/legal_case_document_summarization dataset. It achieves the following results on the evaluation set:
- Loss: 2.7401
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2 | 1.0 | 1924 | 2.8550 |
| 3.6193 | 2.0 | 3848 | 2.7593 |
| 2.7776 | 3.0 | 5772 | 2.7401 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
- Task
- Summarization
- Library
- transformers
- Type
- led
- License
- mit
- Created
- Dec 27, 2023
- Updated
- Jan 11, 2024