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criminal-case-classifier1

Text Classification
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distilbert
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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-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: criminal-case-classifier1
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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
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # criminal-case-classifier1
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8530
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+ - Accuracy: 0.5077
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - training_steps: 300
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.9563 | 0.31 | 10 | 1.1314 | 0.3385 |
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+ | 1.1275 | 0.62 | 20 | 1.0607 | 0.4769 |
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+ | 1.0692 | 0.94 | 30 | 1.0871 | 0.2923 |
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+ | 1.0717 | 1.25 | 40 | 1.1759 | 0.4154 |
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+ | 1.0113 | 1.56 | 50 | 1.1322 | 0.3538 |
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+ | 0.8463 | 1.88 | 60 | 1.1809 | 0.3846 |
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+ | 0.8573 | 2.19 | 70 | 1.0676 | 0.4154 |
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+ | 0.8711 | 2.5 | 80 | 1.0690 | 0.3846 |
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+ | 0.809 | 2.81 | 90 | 1.1253 | 0.4154 |
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+ | 0.7148 | 3.12 | 100 | 1.0913 | 0.4769 |
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+ | 0.5847 | 3.44 | 110 | 1.0920 | 0.5077 |
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+ | 0.5486 | 3.75 | 120 | 1.0597 | 0.5538 |
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+ | 0.5184 | 4.06 | 130 | 1.1016 | 0.4769 |
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+ | 0.2637 | 4.38 | 140 | 1.1908 | 0.4923 |
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+ | 0.3562 | 4.69 | 150 | 1.0238 | 0.5385 |
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+ | 0.3292 | 5.0 | 160 | 1.1011 | 0.5692 |
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+ | 0.1333 | 5.31 | 170 | 1.3049 | 0.5385 |
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+ | 0.1256 | 5.62 | 180 | 1.2819 | 0.5538 |
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+ | 0.1415 | 5.94 | 190 | 1.4929 | 0.5231 |
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+ | 0.0942 | 6.25 | 200 | 1.5290 | 0.5538 |
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+ | 0.0548 | 6.56 | 210 | 1.4844 | 0.5538 |
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+ | 0.0457 | 6.88 | 220 | 1.6174 | 0.5077 |
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+ | 0.0226 | 7.19 | 230 | 1.6499 | 0.5538 |
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+ | 0.032 | 7.5 | 240 | 1.7371 | 0.5077 |
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+ | 0.0158 | 7.81 | 250 | 1.8099 | 0.5385 |
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+ | 0.0244 | 8.12 | 260 | 1.9706 | 0.4769 |
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+ | 0.0134 | 8.44 | 270 | 1.8825 | 0.5231 |
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+ | 0.0117 | 8.75 | 280 | 1.8414 | 0.5077 |
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+ | 0.0111 | 9.06 | 290 | 1.8478 | 0.5077 |
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+ | 0.0107 | 9.38 | 300 | 1.8530 | 0.5077 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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