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tiny_bert_bc_km_5_v1

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distilbert
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README.md ADDED
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+ ---
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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: tiny_bert_bc_km_5_v1
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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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+ # tiny_bert_bc_km_5_v1
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6105
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+ - Accuracy: 0.6830
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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: 0.0001
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+ - train_batch_size: 96
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+ - eval_batch_size: 96
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+ - seed: 10
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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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+ - lr_scheduler_warmup_steps: 10000
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+ - num_epochs: 25
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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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+ | 5.868 | 0.4215 | 10000 | 5.6390 | 0.1587 |
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+ | 5.757 | 0.8431 | 20000 | 5.5611 | 0.1631 |
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+ | 5.6406 | 1.2646 | 30000 | 5.4171 | 0.1782 |
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+ | 3.3457 | 1.6861 | 40000 | 2.9074 | 0.4865 |
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+ | 2.8544 | 2.1077 | 50000 | 2.4903 | 0.5423 |
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+ | 2.5821 | 2.5292 | 60000 | 2.2188 | 0.5786 |
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+ | 2.4361 | 2.9507 | 70000 | 2.0899 | 0.5988 |
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+ | 2.3431 | 3.3723 | 80000 | 2.0070 | 0.6118 |
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+ | 2.2752 | 3.7938 | 90000 | 1.9472 | 0.6216 |
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+ | 2.2181 | 4.2153 | 100000 | 1.9012 | 0.6284 |
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+ | 2.1874 | 4.6369 | 110000 | 1.8619 | 0.6334 |
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+ | 2.1438 | 5.0584 | 120000 | 1.8210 | 0.6391 |
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+ | 2.117 | 5.4799 | 130000 | 1.7991 | 0.6428 |
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+ | 2.1013 | 5.9014 | 140000 | 1.7722 | 0.6463 |
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+ | 2.0674 | 6.3230 | 150000 | 1.7556 | 0.6491 |
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+ | 2.0597 | 6.7445 | 160000 | 1.7411 | 0.6516 |
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+ | 2.0254 | 7.1660 | 170000 | 1.7298 | 0.6539 |
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+ | 2.0177 | 7.5876 | 180000 | 1.7182 | 0.6553 |
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+ | 2.0039 | 8.0091 | 190000 | 1.7304 | 0.6571 |
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+ | 1.9926 | 8.4306 | 200000 | 1.6948 | 0.6593 |
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+ | 1.9789 | 8.8522 | 210000 | 1.6922 | 0.6603 |
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+ | 1.9682 | 9.2737 | 220000 | 1.6792 | 0.6616 |
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+ | 1.9548 | 9.6952 | 230000 | 1.6715 | 0.6629 |
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+ | 1.9364 | 10.1168 | 240000 | 1.6794 | 0.6642 |
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+ | 1.9411 | 10.5383 | 250000 | 1.6578 | 0.6653 |
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+ | 1.9335 | 10.9598 | 260000 | 1.6482 | 0.6665 |
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+ | 1.9191 | 11.3814 | 270000 | 1.6511 | 0.6670 |
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+ | 1.9194 | 11.8029 | 280000 | 1.6416 | 0.6685 |
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+ | 1.9004 | 12.2244 | 290000 | 1.6558 | 0.6690 |
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+ | 1.8987 | 12.6460 | 300000 | 1.6351 | 0.6699 |
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+ | 1.8838 | 13.0675 | 310000 | 1.6363 | 0.6708 |
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+ | 1.8851 | 13.4890 | 320000 | 1.6329 | 0.6713 |
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+ | 1.8829 | 13.9106 | 330000 | 1.6368 | 0.6720 |
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+ | 1.8755 | 14.3321 | 340000 | 1.6218 | 0.6730 |
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+ | 1.8662 | 14.7536 | 350000 | 1.6259 | 0.6733 |
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+ | 1.8555 | 15.1751 | 360000 | 1.6301 | 0.6739 |
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+ | 1.8581 | 15.5967 | 370000 | 1.6150 | 0.6748 |
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+ | 1.8464 | 16.0182 | 380000 | 1.6229 | 0.6753 |
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+ | 1.8441 | 16.4397 | 390000 | 1.6136 | 0.6757 |
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+ | 1.8378 | 16.8613 | 400000 | 1.6066 | 0.6761 |
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+ | 1.8364 | 17.2828 | 410000 | 1.6130 | 0.6770 |
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+ | 1.8323 | 17.7043 | 420000 | 1.6023 | 0.6776 |
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+ | 1.8194 | 18.1259 | 430000 | 1.6100 | 0.6777 |
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+ | 1.8169 | 18.5474 | 440000 | 1.6132 | 0.6779 |
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+ | 1.8174 | 18.9689 | 450000 | 1.6051 | 0.6789 |
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+ | 1.8105 | 19.3905 | 460000 | 1.6220 | 0.6791 |
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+ | 1.8115 | 19.8120 | 470000 | 1.5991 | 0.6795 |
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+ | 1.8015 | 20.2335 | 480000 | 1.6119 | 0.6801 |
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+ | 1.7975 | 20.6551 | 490000 | 1.6027 | 0.6804 |
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+ | 1.7918 | 21.0766 | 500000 | 1.6094 | 0.6808 |
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+ | 1.7896 | 21.4981 | 510000 | 1.6055 | 0.6812 |
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+ | 1.7885 | 21.9197 | 520000 | 1.6038 | 0.6814 |
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+ | 1.7882 | 22.3412 | 530000 | 1.6068 | 0.6816 |
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+ | 1.7826 | 22.7627 | 540000 | 1.6105 | 0.6819 |
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+ | 1.7816 | 23.1843 | 550000 | 1.6100 | 0.6822 |
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+ | 1.7788 | 23.6058 | 560000 | 1.6041 | 0.6828 |
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+ | 1.772 | 24.0273 | 570000 | 1.6118 | 0.6827 |
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+ | 1.7736 | 24.4488 | 580000 | 1.6020 | 0.6835 |
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+ | 1.7698 | 24.8704 | 590000 | 1.6105 | 0.6830 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.19.1
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