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HBERTv1_emb_compress_48_L12_H256_A4

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hybridbert
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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: HBERTv1_emb_compress_48_L12_H256_A4
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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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+ # HBERTv1_emb_compress_48_L12_H256_A4
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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: 6.0468
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+ - Accuracy: 0.1510
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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: 1e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 10
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+ - distributed_type: multi-GPU
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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: 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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+ | 7.1159 | 0.11 | 10000 | 7.0948 | 0.0805 |
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+ | 6.698 | 0.22 | 20000 | 6.6913 | 0.1060 |
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+ | 6.5481 | 0.33 | 30000 | 6.5473 | 0.1167 |
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+ | 6.4589 | 0.44 | 40000 | 6.4576 | 0.1252 |
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+ | 6.3925 | 0.55 | 50000 | 6.3858 | 0.1306 |
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+ | 6.3433 | 0.66 | 60000 | 6.3356 | 0.1353 |
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+ | 6.2983 | 0.76 | 70000 | 6.2965 | 0.1376 |
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+ | 6.268 | 0.87 | 80000 | 6.2643 | 0.1397 |
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+ | 6.2359 | 0.98 | 90000 | 6.2381 | 0.1411 |
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+ | 6.2186 | 1.09 | 100000 | 6.2160 | 0.1429 |
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+ | 6.1915 | 1.2 | 110000 | 6.1972 | 0.1439 |
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+ | 6.1811 | 1.31 | 120000 | 6.1834 | 0.1440 |
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+ | 6.1696 | 1.42 | 130000 | 6.1692 | 0.1455 |
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+ | 6.1621 | 1.53 | 140000 | 6.1557 | 0.1454 |
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+ | 6.1417 | 1.64 | 150000 | 6.1466 | 0.1468 |
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+ | 6.1391 | 1.75 | 160000 | 6.1364 | 0.1466 |
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+ | 6.1338 | 1.86 | 170000 | 6.1281 | 0.1476 |
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+ | 6.1285 | 1.97 | 180000 | 6.1200 | 0.1477 |
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+ | 6.1147 | 2.08 | 190000 | 6.1135 | 0.1483 |
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+ | 6.1139 | 2.18 | 200000 | 6.1083 | 0.1486 |
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+ | 6.1004 | 2.29 | 210000 | 6.1004 | 0.1487 |
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+ | 6.0997 | 2.4 | 220000 | 6.0964 | 0.1489 |
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+ | 6.092 | 2.51 | 230000 | 6.0922 | 0.1490 |
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+ | 6.089 | 2.62 | 240000 | 6.0862 | 0.1490 |
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+ | 6.0841 | 2.73 | 250000 | 6.0829 | 0.1498 |
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+ | 6.0847 | 2.84 | 260000 | 6.0799 | 0.1496 |
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+ | 6.0834 | 2.95 | 270000 | 6.0760 | 0.1501 |
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+ | 6.0752 | 3.06 | 280000 | 6.0715 | 0.1502 |
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+ | 6.0693 | 3.17 | 290000 | 6.0697 | 0.1502 |
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+ | 6.0677 | 3.28 | 300000 | 6.0679 | 0.1502 |
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+ | 6.0646 | 3.39 | 310000 | 6.0646 | 0.1503 |
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+ | 6.0625 | 3.5 | 320000 | 6.0623 | 0.1503 |
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+ | 6.0536 | 3.6 | 330000 | 6.0593 | 0.1507 |
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+ | 6.0574 | 3.71 | 340000 | 6.0577 | 0.1507 |
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+ | 6.0496 | 3.82 | 350000 | 6.0560 | 0.1508 |
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+ | 6.0525 | 3.93 | 360000 | 6.0543 | 0.1507 |
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+ | 6.0498 | 4.04 | 370000 | 6.0508 | 0.1509 |
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+ | 6.0557 | 4.15 | 380000 | 6.0509 | 0.1508 |
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+ | 6.0445 | 4.26 | 390000 | 6.0483 | 0.1509 |
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+ | 6.0466 | 4.37 | 400000 | 6.0470 | 0.1510 |
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+ | 6.0507 | 4.48 | 410000 | 6.0471 | 0.1510 |
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+ | 6.0459 | 4.59 | 420000 | 6.0468 | 0.1510 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3