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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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+ model-index:
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+ - name: discord_classification2
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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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+ # discord_classification2
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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: 0.0020
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+ - Accuracy: 1.0
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+ - Auc: 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: 0.0002
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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: 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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+ - num_epochs: 10
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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 | Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
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+ | 0.1484 | 1.0 | 92 | 0.0125 | 1.0 | 1.0 |
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+ | 0.0164 | 2.0 | 184 | 0.0086 | 1.0 | 1.0 |
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+ | 0.0138 | 3.0 | 276 | 0.0038 | 1.0 | 1.0 |
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+ | 0.0073 | 4.0 | 368 | 0.0095 | 0.989 | 1.0 |
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+ | 0.0052 | 5.0 | 460 | 0.0023 | 1.0 | 1.0 |
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+ | 0.0065 | 6.0 | 552 | 0.0021 | 1.0 | 1.0 |
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+ | 0.0041 | 7.0 | 644 | 0.0018 | 1.0 | 1.0 |
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+ | 0.0062 | 8.0 | 736 | 0.0023 | 1.0 | 1.0 |
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+ | 0.0032 | 9.0 | 828 | 0.0020 | 1.0 | 1.0 |
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+ | 0.0044 | 10.0 | 920 | 0.0020 | 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 4.47.0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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