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tiny_bert_bc_rand_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_rand_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_rand_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: 3.2519
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+ - Accuracy: 0.6859
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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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+ | 7.2824 | 0.4215 | 10000 | 7.1207 | 0.1583 |
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+ | 7.1705 | 0.8431 | 20000 | 6.9795 | 0.1726 |
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+ | 4.6634 | 1.2646 | 30000 | 4.2812 | 0.5084 |
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+ | 4.2844 | 1.6861 | 40000 | 3.9252 | 0.5556 |
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+ | 4.0555 | 2.1077 | 50000 | 3.7210 | 0.5845 |
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+ | 3.9068 | 2.5292 | 60000 | 3.5822 | 0.6047 |
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+ | 3.8047 | 2.9507 | 70000 | 3.4940 | 0.6183 |
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+ | 3.734 | 3.3723 | 80000 | 3.4309 | 0.6281 |
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+ | 3.678 | 3.7938 | 90000 | 3.3727 | 0.6365 |
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+ | 3.6347 | 4.2153 | 100000 | 3.3363 | 0.6426 |
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+ | 3.6013 | 4.6369 | 110000 | 3.3058 | 0.6471 |
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+ | 3.5724 | 5.0584 | 120000 | 3.2759 | 0.6515 |
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+ | 3.5458 | 5.4799 | 130000 | 3.2562 | 0.6551 |
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+ | 3.53 | 5.9014 | 140000 | 3.2334 | 0.6588 |
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+ | 3.5054 | 6.3230 | 150000 | 3.2178 | 0.6610 |
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+ | 3.4971 | 6.7445 | 160000 | 3.2043 | 0.6632 |
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+ | 3.4724 | 7.1660 | 170000 | 3.1913 | 0.6659 |
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+ | 3.4615 | 7.5876 | 180000 | 3.1805 | 0.6671 |
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+ | 3.4516 | 8.0091 | 190000 | 3.1677 | 0.6690 |
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+ | 3.4405 | 8.4306 | 200000 | 3.1585 | 0.6710 |
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+ | 3.4284 | 8.8522 | 210000 | 3.1508 | 0.6722 |
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+ | 3.4212 | 9.2737 | 220000 | 3.1426 | 0.6731 |
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+ | 3.4078 | 9.6952 | 230000 | 3.1356 | 0.6746 |
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+ | 3.3963 | 10.1168 | 240000 | 3.1310 | 0.6762 |
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+ | 3.3982 | 10.5383 | 250000 | 3.1214 | 0.6771 |
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+ | 3.3879 | 10.9598 | 260000 | 3.1157 | 0.6781 |
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+ | 3.3778 | 11.3814 | 270000 | 3.1170 | 0.6780 |
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+ | 3.3824 | 11.8029 | 280000 | 3.1097 | 0.6796 |
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+ | 3.3619 | 12.2244 | 290000 | 3.1111 | 0.6801 |
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+ | 3.3641 | 12.6460 | 300000 | 3.1050 | 0.6809 |
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+ | 3.3471 | 13.0675 | 310000 | 3.1109 | 0.6812 |
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+ | 3.3512 | 13.4890 | 320000 | 3.1056 | 0.6817 |
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+ | 3.3523 | 13.9106 | 330000 | 3.1034 | 0.6820 |
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+ | 3.3385 | 14.3321 | 340000 | 3.1033 | 0.6824 |
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+ | 3.3393 | 14.7536 | 350000 | 3.1061 | 0.6828 |
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+ | 3.3183 | 15.1751 | 360000 | 3.1164 | 0.6829 |
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+ | 3.3261 | 15.5967 | 370000 | 3.1082 | 0.6833 |
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+ | 3.2993 | 16.0182 | 380000 | 3.1230 | 0.6837 |
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+ | 3.3079 | 16.4397 | 390000 | 3.1179 | 0.6836 |
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+ | 3.3071 | 16.8613 | 400000 | 3.1099 | 0.6837 |
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+ | 3.2867 | 17.2828 | 410000 | 3.1292 | 0.6843 |
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+ | 3.2879 | 17.7043 | 420000 | 3.1274 | 0.6841 |
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+ | 3.2591 | 18.1259 | 430000 | 3.1492 | 0.6841 |
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+ | 3.265 | 18.5474 | 440000 | 3.1469 | 0.6839 |
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+ | 3.2726 | 18.9689 | 450000 | 3.1432 | 0.6846 |
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+ | 3.2429 | 19.3905 | 460000 | 3.1709 | 0.6847 |
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+ | 3.2518 | 19.8120 | 470000 | 3.1598 | 0.6846 |
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+ | 3.2136 | 20.2335 | 480000 | 3.1932 | 0.6846 |
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+ | 3.2214 | 20.6551 | 490000 | 3.1829 | 0.6848 |
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+ | 3.1855 | 21.0766 | 500000 | 3.1981 | 0.6848 |
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+ | 3.1918 | 21.4981 | 510000 | 3.2118 | 0.6851 |
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+ | 3.2026 | 21.9197 | 520000 | 3.1942 | 0.6851 |
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+ | 3.1785 | 22.3412 | 530000 | 3.2237 | 0.6851 |
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+ | 3.1744 | 22.7627 | 540000 | 3.2269 | 0.6853 |
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+ | 3.1528 | 23.1843 | 550000 | 3.2419 | 0.6853 |
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+ | 3.155 | 23.6058 | 560000 | 3.2405 | 0.6858 |
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+ | 3.1321 | 24.0273 | 570000 | 3.2574 | 0.6859 |
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+ | 3.1351 | 24.4488 | 580000 | 3.2498 | 0.6862 |
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+ | 3.133 | 24.8704 | 590000 | 3.2519 | 0.6859 |
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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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