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nzm97
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math_question_grade_detection_v12

Text Classification
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Initial model push after training

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  1. README.md +96 -0
  2. config.json +117 -0
  3. model.safetensors +3 -0
  4. runs/Dec12_08-26-45_3fa1ca6bfc57/events.out.tfevents.1733992023.3fa1ca6bfc57.23.0 +3 -0
  5. runs/Dec12_08-46-32_8902b8b9ab3c/events.out.tfevents.1733993195.8902b8b9ab3c.23.0 +3 -0
  6. training_args.bin +3 -0
README.md ADDED
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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: google-bert/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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: math_question_grade_detection_v12
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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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+ # math_question_grade_detection_v12
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8913
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+ - Accuracy: 0.7397
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+ - Precision: 0.7255
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+ - Recall: 0.7397
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+ - F1: 0.7178
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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: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use 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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+ - training_steps: 1500
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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 | Precision | Recall | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.0855 | 50 | 3.0343 | 0.1710 | 0.1287 | 0.1710 | 0.0917 |
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+ | No log | 0.1709 | 100 | 2.4792 | 0.3151 | 0.2979 | 0.3151 | 0.2439 |
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+ | No log | 0.2564 | 150 | 2.1397 | 0.4428 | 0.4101 | 0.4428 | 0.3752 |
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+ | No log | 0.3419 | 200 | 1.9824 | 0.4419 | 0.3872 | 0.4419 | 0.3638 |
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+ | No log | 0.4274 | 250 | 1.7765 | 0.5072 | 0.4772 | 0.5072 | 0.4666 |
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+ | No log | 0.5128 | 300 | 1.6510 | 0.5524 | 0.5347 | 0.5524 | 0.5147 |
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+ | No log | 0.5983 | 350 | 1.5160 | 0.5793 | 0.5501 | 0.5793 | 0.5319 |
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+ | No log | 0.6838 | 400 | 1.4481 | 0.5898 | 0.5608 | 0.5898 | 0.5437 |
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+ | No log | 0.7692 | 450 | 1.3791 | 0.6148 | 0.5758 | 0.6148 | 0.5678 |
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+ | 1.9748 | 0.8547 | 500 | 1.3154 | 0.6196 | 0.6123 | 0.6196 | 0.5779 |
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+ | 1.9748 | 0.9402 | 550 | 1.2399 | 0.6484 | 0.6168 | 0.6484 | 0.6119 |
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+ | 1.9748 | 1.0256 | 600 | 1.1968 | 0.6340 | 0.6181 | 0.6340 | 0.5889 |
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+ | 1.9748 | 1.1111 | 650 | 1.2477 | 0.6215 | 0.6014 | 0.6215 | 0.5825 |
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+ | 1.9748 | 1.1966 | 700 | 1.2098 | 0.6340 | 0.6285 | 0.6340 | 0.5884 |
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+ | 1.9748 | 1.2821 | 750 | 1.1316 | 0.6619 | 0.6442 | 0.6619 | 0.6385 |
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+ | 1.9748 | 1.3675 | 800 | 1.0783 | 0.6744 | 0.6644 | 0.6744 | 0.6462 |
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+ | 1.9748 | 1.4530 | 850 | 1.0512 | 0.6907 | 0.6728 | 0.6907 | 0.6583 |
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+ | 1.9748 | 1.5385 | 900 | 1.0388 | 0.6945 | 0.6909 | 0.6945 | 0.6697 |
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+ | 1.9748 | 1.6239 | 950 | 0.9954 | 0.6974 | 0.6748 | 0.6974 | 0.6707 |
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+ | 1.0265 | 1.7094 | 1000 | 0.9812 | 0.7128 | 0.6888 | 0.7128 | 0.6874 |
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+ | 1.0265 | 1.7949 | 1050 | 0.9717 | 0.7099 | 0.6907 | 0.7099 | 0.6852 |
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+ | 1.0265 | 1.8803 | 1100 | 0.9437 | 0.7099 | 0.6823 | 0.7099 | 0.6866 |
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+ | 1.0265 | 1.9658 | 1150 | 0.9724 | 0.7061 | 0.7096 | 0.7061 | 0.6800 |
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+ | 1.0265 | 2.0513 | 1200 | 0.9168 | 0.7224 | 0.7099 | 0.7224 | 0.6976 |
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+ | 1.0265 | 2.1368 | 1250 | 0.9097 | 0.7243 | 0.7109 | 0.7243 | 0.6996 |
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+ | 1.0265 | 2.2222 | 1300 | 0.9072 | 0.7329 | 0.7336 | 0.7329 | 0.7083 |
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+ | 1.0265 | 2.3077 | 1350 | 0.9028 | 0.7262 | 0.7114 | 0.7262 | 0.7033 |
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+ | 1.0265 | 2.3932 | 1400 | 0.8951 | 0.7301 | 0.7145 | 0.7301 | 0.7068 |
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+ | 1.0265 | 2.4786 | 1450 | 0.8949 | 0.7378 | 0.7339 | 0.7378 | 0.7154 |
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+ | 0.687 | 2.5641 | 1500 | 0.8913 | 0.7397 | 0.7255 | 0.7397 | 0.7178 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.4.0
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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