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sasingh192
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minilm-finetuned-movie

Text Classification
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PyTorch
bert
Generated from Trainer
Inference Endpoints
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: minilm-finetuned-movie
    results: []

minilm-finetuned-movie

This model is a fine-tuned version of microsoft/miniLM-L12-H384-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0451
  • F1: 0.9856

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
0.9623 1.0 1946 0.7742 0.6985
0.7969 2.0 3892 0.7289 0.7094
0.74 3.0 5838 0.6479 0.7476
0.7012 4.0 7784 0.6263 0.7550
0.6689 5.0 9730 0.5823 0.7762
0.6416 6.0 11676 0.5796 0.7673
0.6149 7.0 13622 0.5324 0.7912
0.5939 8.0 15568 0.5189 0.7986
0.5714 9.0 17514 0.4793 0.8184
0.5495 10.0 19460 0.4566 0.8249
0.5297 11.0 21406 0.4155 0.8475
0.5101 12.0 23352 0.4063 0.8494
0.4924 13.0 25298 0.3829 0.8571
0.4719 14.0 27244 0.4032 0.8449
0.4552 15.0 29190 0.3447 0.8720
0.4382 16.0 31136 0.3581 0.8610
0.421 17.0 33082 0.3095 0.8835
0.4038 18.0 35028 0.2764 0.9002
0.3883 19.0 36974 0.2610 0.9051
0.3745 20.0 38920 0.2533 0.9064
0.3616 21.0 40866 0.2601 0.9005
0.345 22.0 42812 0.2085 0.9267
0.3314 23.0 44758 0.2421 0.9069
0.3178 24.0 46704 0.2006 0.9268
0.3085 25.0 48650 0.1846 0.9326
0.2964 26.0 50596 0.1492 0.9490
0.2855 27.0 52542 0.1664 0.9376
0.2737 28.0 54488 0.1309 0.9560
0.2641 29.0 56434 0.1318 0.9562
0.2541 30.0 58380 0.1490 0.9440
0.2462 31.0 60326 0.1195 0.9575
0.234 32.0 62272 0.1054 0.9640
0.2273 33.0 64218 0.1054 0.9631
0.2184 34.0 66164 0.0971 0.9662
0.214 35.0 68110 0.0902 0.9689
0.2026 36.0 70056 0.0846 0.9699
0.1973 37.0 72002 0.0819 0.9705
0.1934 38.0 73948 0.0810 0.9716
0.1884 39.0 75894 0.0724 0.9746
0.1796 40.0 77840 0.0737 0.9743
0.1779 41.0 79786 0.0665 0.9773
0.1703 42.0 81732 0.0568 0.9811
0.1638 43.0 83678 0.0513 0.9843
0.1601 44.0 85624 0.0575 0.9802
0.1593 45.0 87570 0.0513 0.9835
0.1559 46.0 89516 0.0474 0.9851
0.1514 47.0 91462 0.0477 0.9847
0.1473 48.0 93408 0.0444 0.9858
0.1462 49.0 95354 0.0449 0.9855
0.1458 50.0 97300 0.0451 0.9856

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1
  • Datasets 2.12.0
  • Tokenizers 0.13.2