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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: 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: roberta-truncated-echr_facts_all_labels_lora
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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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+ # roberta-truncated-echr_facts_all_labels_lora
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0727
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+ - F1: 0.7452
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+ - Roc Auc: 0.8539
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+ - Accuracy: 0.5908
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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: 4
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+ - eval_batch_size: 4
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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: 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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+ | 0.0678 | 1.0 | 3530 | 0.0698 | 0.7213 | 0.8258 | 0.5341 |
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+ | 0.0581 | 2.0 | 7060 | 0.0663 | 0.7339 | 0.8334 | 0.5711 |
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+ | 0.0493 | 3.0 | 10590 | 0.0691 | 0.7381 | 0.8435 | 0.5825 |
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+ | 0.0415 | 4.0 | 14120 | 0.0727 | 0.7452 | 0.8539 | 0.5908 |
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+ | 0.0326 | 5.0 | 17650 | 0.0761 | 0.7364 | 0.8480 | 0.5774 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.14.5
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+ - Tokenizers 0.15.1
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