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Training completed!

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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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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: reporting-multiclass
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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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+ # reporting-multiclass
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1098
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+ - F1: 1.0
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+ - Roc Auc: 1.0
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+ - Accuracy: 1.0
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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: 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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+ - num_epochs: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.5931 | 1.0 | 33 | 0.4546 | 0.3988 | 0.6313 | 0.0 |
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+ | 0.4492 | 2.0 | 66 | 0.3765 | 0.4629 | 0.6625 | 0.0446 |
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+ | 0.3941 | 3.0 | 99 | 0.3113 | 0.6222 | 0.7403 | 0.0893 |
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+ | 0.3004 | 4.0 | 132 | 0.2589 | 0.7948 | 0.8383 | 0.375 |
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+ | 0.2581 | 5.0 | 165 | 0.2200 | 0.8741 | 0.8935 | 0.6071 |
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+ | 0.2375 | 6.0 | 198 | 0.1922 | 0.9129 | 0.9302 | 0.6875 |
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+ | 0.1881 | 7.0 | 231 | 0.1711 | 0.9333 | 0.9375 | 0.75 |
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+ | 0.1806 | 8.0 | 264 | 0.1546 | 0.9390 | 0.9456 | 0.7857 |
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+ | 0.164 | 9.0 | 297 | 0.1412 | 0.9654 | 0.9665 | 0.8661 |
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+ | 0.1466 | 10.0 | 330 | 0.1309 | 0.9654 | 0.9665 | 0.8661 |
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+ | 0.1318 | 11.0 | 363 | 0.1229 | 0.9772 | 0.9777 | 0.9107 |
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+ | 0.13 | 12.0 | 396 | 0.1169 | 0.9933 | 0.9933 | 0.9732 |
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+ | 0.1225 | 13.0 | 429 | 0.1129 | 1.0 | 1.0 | 1.0 |
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+ | 0.1165 | 14.0 | 462 | 0.1106 | 1.0 | 1.0 | 1.0 |
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+ | 0.1215 | 15.0 | 495 | 0.1098 | 1.0 | 1.0 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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