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End of training

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README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ base_model: s2w-ai/DarkBERT
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: DarkBERT-finetuned-ner
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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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+ # DarkBERT-finetuned-ner
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+
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+ This model is a fine-tuned version of [s2w-ai/DarkBERT](https://huggingface.co/s2w-ai/DarkBERT) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6416
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+ - Precision: 0.4628
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+ - Recall: 0.5470
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+ - F1: 0.5014
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+ - Accuracy: 0.8901
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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: 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 | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 111 | 0.3933 | 0.3563 | 0.4337 | 0.3912 | 0.8726 |
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+ | No log | 2.0 | 222 | 0.3491 | 0.4345 | 0.5672 | 0.4921 | 0.8886 |
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+ | No log | 3.0 | 333 | 0.3991 | 0.4284 | 0.5405 | 0.4780 | 0.8795 |
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+ | No log | 4.0 | 444 | 0.3969 | 0.4565 | 0.5797 | 0.5108 | 0.8877 |
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+ | 0.2744 | 5.0 | 555 | 0.4276 | 0.4737 | 0.5690 | 0.5170 | 0.8887 |
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+ | 0.2744 | 6.0 | 666 | 0.5237 | 0.4918 | 0.5637 | 0.5253 | 0.8862 |
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+ | 0.2744 | 7.0 | 777 | 0.5472 | 0.4855 | 0.5503 | 0.5159 | 0.8877 |
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+ | 0.2744 | 8.0 | 888 | 0.6319 | 0.4581 | 0.5699 | 0.5079 | 0.8855 |
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+ | 0.2744 | 9.0 | 999 | 0.6511 | 0.4901 | 0.5744 | 0.5289 | 0.8901 |
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+ | 0.0627 | 10.0 | 1110 | 0.6758 | 0.4900 | 0.5681 | 0.5262 | 0.8899 |
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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 2.21.0
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+ - Tokenizers 0.19.1
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