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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: topic-legal-bert-base-uncased-supreme-court-16batch_3epoch_2e5lr_01wd
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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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# topic-legal-bert-base-uncased-supreme-court-16batch_3epoch_2e5lr_01wd
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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: 0.7456
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- Accuracy: 0.7784
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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: 16
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- eval_batch_size: 16
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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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| 0.8618 | 1.0 | 1319 | 0.7770 | 0.7625 |
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| 0.5796 | 2.0 | 2638 | 0.7247 | 0.7821 |
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| 0.4043 | 3.0 | 3957 | 0.7456 | 0.7784 |
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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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runs/Dec03_20-12-28_gr048.hpc.nyu.edu/events.out.tfevents.1701652348.gr048.hpc.nyu.edu.1713208.0
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