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End of training

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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: answerdotai/ModernBERT-base
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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: Assignment4_Distilled_ModernBERT
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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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+ # Assignment4_Distilled_ModernBERT
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+
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+ This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2589
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+ - Accuracy: 0.9681
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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: 6e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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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 | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 7.8963 | 0.2096 | 100 | 2.9564 | 0.7577 |
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+ | 1.6375 | 0.4193 | 200 | 1.0919 | 0.8806 |
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+ | 0.8239 | 0.6289 | 300 | 0.6403 | 0.9335 |
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+ | 0.5738 | 0.8386 | 400 | 0.5019 | 0.9448 |
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+ | 0.3915 | 1.0482 | 500 | 0.4918 | 0.9452 |
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+ | 0.1938 | 1.2579 | 600 | 0.4370 | 0.9548 |
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+ | 0.2045 | 1.4675 | 700 | 0.4937 | 0.9435 |
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+ | 0.1874 | 1.6771 | 800 | 0.4477 | 0.9568 |
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+ | 0.1804 | 1.8868 | 900 | 0.4118 | 0.9581 |
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+ | 0.1237 | 2.0964 | 1000 | 0.3573 | 0.9616 |
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+ | 0.076 | 2.3061 | 1100 | 0.3772 | 0.9574 |
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+ | 0.0834 | 2.5157 | 1200 | 0.3337 | 0.9652 |
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+ | 0.0713 | 2.7254 | 1300 | 0.3032 | 0.9658 |
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+ | 0.0514 | 2.9350 | 1400 | 0.3009 | 0.9661 |
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+ | 0.0448 | 3.1447 | 1500 | 0.2892 | 0.9661 |
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+ | 0.0425 | 3.3543 | 1600 | 0.2864 | 0.9671 |
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+ | 0.0341 | 3.5639 | 1700 | 0.2859 | 0.9642 |
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+ | 0.0389 | 3.7736 | 1800 | 0.2763 | 0.9677 |
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+ | 0.0409 | 3.9832 | 1900 | 0.2682 | 0.9668 |
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+ | 0.0266 | 4.1929 | 2000 | 0.2624 | 0.9674 |
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+ | 0.0265 | 4.4025 | 2100 | 0.2610 | 0.9684 |
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+ | 0.0267 | 4.6122 | 2200 | 0.2592 | 0.9684 |
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+ | 0.027 | 4.8218 | 2300 | 0.2589 | 0.9681 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.0
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.1
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