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sasingh192
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minilm-finetuned-movie

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: minilm-finetuned-movie
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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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+ # minilm-finetuned-movie
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+
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+ This model is a fine-tuned version of [microsoft/miniLM-L12-H384-uncased](https://huggingface.co/microsoft/miniLM-L12-H384-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0451
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+ - F1: 0.9856
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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: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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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: 50
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 0.9623 | 1.0 | 1946 | 0.7742 | 0.6985 |
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+ | 0.7969 | 2.0 | 3892 | 0.7289 | 0.7094 |
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+ | 0.74 | 3.0 | 5838 | 0.6479 | 0.7476 |
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+ | 0.7012 | 4.0 | 7784 | 0.6263 | 0.7550 |
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+ | 0.6689 | 5.0 | 9730 | 0.5823 | 0.7762 |
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+ | 0.6416 | 6.0 | 11676 | 0.5796 | 0.7673 |
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+ | 0.6149 | 7.0 | 13622 | 0.5324 | 0.7912 |
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+ | 0.5939 | 8.0 | 15568 | 0.5189 | 0.7986 |
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+ | 0.5714 | 9.0 | 17514 | 0.4793 | 0.8184 |
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+ | 0.5495 | 10.0 | 19460 | 0.4566 | 0.8249 |
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+ | 0.5297 | 11.0 | 21406 | 0.4155 | 0.8475 |
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+ | 0.5101 | 12.0 | 23352 | 0.4063 | 0.8494 |
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+ | 0.4924 | 13.0 | 25298 | 0.3829 | 0.8571 |
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+ | 0.4719 | 14.0 | 27244 | 0.4032 | 0.8449 |
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+ | 0.4552 | 15.0 | 29190 | 0.3447 | 0.8720 |
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+ | 0.4382 | 16.0 | 31136 | 0.3581 | 0.8610 |
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+ | 0.421 | 17.0 | 33082 | 0.3095 | 0.8835 |
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+ | 0.4038 | 18.0 | 35028 | 0.2764 | 0.9002 |
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+ | 0.3883 | 19.0 | 36974 | 0.2610 | 0.9051 |
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+ | 0.3745 | 20.0 | 38920 | 0.2533 | 0.9064 |
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+ | 0.3616 | 21.0 | 40866 | 0.2601 | 0.9005 |
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+ | 0.345 | 22.0 | 42812 | 0.2085 | 0.9267 |
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+ | 0.3314 | 23.0 | 44758 | 0.2421 | 0.9069 |
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+ | 0.3178 | 24.0 | 46704 | 0.2006 | 0.9268 |
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+ | 0.3085 | 25.0 | 48650 | 0.1846 | 0.9326 |
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+ | 0.2964 | 26.0 | 50596 | 0.1492 | 0.9490 |
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+ | 0.2855 | 27.0 | 52542 | 0.1664 | 0.9376 |
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+ | 0.2737 | 28.0 | 54488 | 0.1309 | 0.9560 |
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+ | 0.2641 | 29.0 | 56434 | 0.1318 | 0.9562 |
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+ | 0.2541 | 30.0 | 58380 | 0.1490 | 0.9440 |
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+ | 0.2462 | 31.0 | 60326 | 0.1195 | 0.9575 |
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+ | 0.234 | 32.0 | 62272 | 0.1054 | 0.9640 |
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+ | 0.2273 | 33.0 | 64218 | 0.1054 | 0.9631 |
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+ | 0.2184 | 34.0 | 66164 | 0.0971 | 0.9662 |
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+ | 0.214 | 35.0 | 68110 | 0.0902 | 0.9689 |
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+ | 0.2026 | 36.0 | 70056 | 0.0846 | 0.9699 |
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+ | 0.1973 | 37.0 | 72002 | 0.0819 | 0.9705 |
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+ | 0.1934 | 38.0 | 73948 | 0.0810 | 0.9716 |
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+ | 0.1884 | 39.0 | 75894 | 0.0724 | 0.9746 |
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+ | 0.1796 | 40.0 | 77840 | 0.0737 | 0.9743 |
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+ | 0.1779 | 41.0 | 79786 | 0.0665 | 0.9773 |
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+ | 0.1703 | 42.0 | 81732 | 0.0568 | 0.9811 |
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+ | 0.1638 | 43.0 | 83678 | 0.0513 | 0.9843 |
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+ | 0.1601 | 44.0 | 85624 | 0.0575 | 0.9802 |
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+ | 0.1593 | 45.0 | 87570 | 0.0513 | 0.9835 |
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+ | 0.1559 | 46.0 | 89516 | 0.0474 | 0.9851 |
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+ | 0.1514 | 47.0 | 91462 | 0.0477 | 0.9847 |
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+ | 0.1473 | 48.0 | 93408 | 0.0444 | 0.9858 |
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+ | 0.1462 | 49.0 | 95354 | 0.0449 | 0.9855 |
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+ | 0.1458 | 50.0 | 97300 | 0.0451 | 0.9856 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 2.0.1
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2