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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: answerdotai/ModernBERT-large
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: Docket_Classification_NER_04_15
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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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# Docket_Classification_NER_04_15
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5623
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- Precision: 0.8737
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- Recall: 0.8823
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- F1: 0.8760
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|
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| No log | 1.0 | 21 | 0.4220 | 0.8540 | 0.8819 | 0.8621 |
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| No log | 2.0 | 42 | 0.4700 | 0.8680 | 0.8596 | 0.8620 |
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| No log | 3.0 | 63 | 0.4701 | 0.8683 | 0.8705 | 0.8682 |
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| No log | 4.0 | 84 | 0.5636 | 0.8680 | 0.8765 | 0.8698 |
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| No log | 4.7901 | 100 | 0.5623 | 0.8737 | 0.8823 | 0.8760 |
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### Framework versions
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- Transformers 4.51.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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