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Training completed!

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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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: fold_4_model_roberta
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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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+ # fold_4_model_roberta
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5913
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+ - F1: 0.7350
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+ - Roc Auc: 0.8008
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+ - Accuracy: 0.3874
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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 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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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 5
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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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+ | 0.0681 | 1.0 | 111 | 0.5913 | 0.7350 | 0.8008 | 0.3874 |
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+ | 0.0297 | 2.0 | 222 | 0.6022 | 0.7263 | 0.7955 | 0.3694 |
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+ | 0.0258 | 3.0 | 333 | 0.6772 | 0.7169 | 0.7854 | 0.3784 |
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+ | 0.0228 | 4.0 | 444 | 0.6766 | 0.7298 | 0.7982 | 0.3784 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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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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+ "layer_norm_eps": 1e-05,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "multi_label_classification",
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