annabellehuether
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Training completed!
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README.md
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---
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license: cc-by-sa-4.0
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base_model: nlpaueb/legal-bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: legal-bert-base-uncased-supreme-court-batch64
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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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# legal-bert-base-uncased-supreme-court-batch64
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This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5612
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- Accuracy: 0.6489
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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: 64
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- eval_batch_size: 64
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- seed: 7
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 330 | 0.5572 | 0.6356 |
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| 0.6367 | 2.0 | 660 | 0.5603 | 0.6426 |
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| 0.6367 | 3.0 | 990 | 0.5612 | 0.6489 |
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### Framework versions
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- Transformers 4.35.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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