| | ---
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| | library_name: transformers
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| | license: apache-2.0
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| | base_model: distilbert/distilbert-base-uncased
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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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| | - accuracy
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| | model-index:
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| | - name: TokenClassifierModel
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| | results: []
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| | ---
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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
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
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| | # TokenClassifierModel
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| |
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| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 0.3167
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| | - Precision: 0.3447
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| | - Recall: 0.2910
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| | - F1: 0.3156
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| | - Accuracy: 0.9336
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
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| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
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| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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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: 42
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| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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| | - num_epochs: 2
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| | | No log | 1.0 | 77 | 0.3453 | 0.2878 | 0.1075 | 0.1565 | 0.9291 |
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| | | No log | 2.0 | 154 | 0.3167 | 0.3447 | 0.2910 | 0.3156 | 0.9336 |
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| |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.55.3
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| | - Pytorch 2.8.0+cpu
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| | - Datasets 4.0.0
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| | - Tokenizers 0.21.4
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| | |
