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tjl223/song-artist-classifier-v4-roberta-batch-8

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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song-artist-classifier-v4-roberta-batch-8

This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0933
  • —F1: [0.7777777777777777, 0.75, 0.7, 0.9473684210526316, 1.0, 0.30769230769230765, 0.9090909090909091, 0.7368421052631577, 0.5217391304347826, 0.8000000000000002, 0.25, 0.761904761904762, 0.6923076923076923, 0.7499999999999999, 0.5, 0.5263157894736842, 0.8421052631578948, 0.8421052631578948, 0.5333333333333333, 0.4347826086956522]

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossF1
No log1.01902.1347[0.3478260869565218, 0.25, 0.26666666666666666, 0.47619047619047616, 0.0, 0.0, 0.18181818181818182, 0.5384615384615384, 0.0, 0.625, 0.0, 0.2222222222222222, 0.33333333333333326, 0.4444444444444445, 0.22222222222222224, 0.5833333333333334, 0.3478260869565218, 0.6923076923076923, 0.4210526315789474, 0.14285714285714288]
No log2.03801.5541[0.7368421052631577, 0.14285714285714285, 0.5, 0.4347826086956522, 0.6666666666666666, 0.5, 0.6666666666666666, 0.37499999999999994, 0.3333333333333333, 0.6666666666666666, 0.0, 0.5882352941176471, 0.6666666666666666, 0.6666666666666666, 0.5714285714285713, 0.64, 0.6363636363636365, 0.888888888888889, 0.38461538461538464, 0.45454545454545453]
1.96583.05701.2774[0.7777777777777777, 0.47058823529411764, 0.608695652173913, 0.6, 0.8571428571428571, 0.28571428571428575, 0.7692307692307693, 0.7272727272727272, 0.2727272727272727, 0.7, 0.0, 0.5555555555555556, 0.75, 0.6666666666666666, 0.6, 0.6666666666666666, 0.5185185185185185, 0.8000000000000002, 0.5333333333333333, 0.4000000000000001]
1.96584.07601.1606[0.761904761904762, 0.64, 0.6666666666666666, 0.5, 0.8571428571428571, 0.16666666666666669, 0.8181818181818182, 0.7368421052631577, 0.5, 0.761904761904762, 0.18181818181818182, 0.7777777777777777, 0.8421052631578948, 0.7499999999999999, 0.43243243243243246, 0.6666666666666666, 0.7777777777777777, 0.888888888888889, 0.5714285714285715, 0.37499999999999994]
1.96585.09501.2332[0.608695652173913, 0.6666666666666667, 0.7368421052631577, 0.8235294117647058, 0.888888888888889, 0.5, 0.9, 0.7368421052631577, 0.4615384615384615, 0.7499999999999999, 0.125, 0.7272727272727273, 0.8000000000000002, 0.7499999999999999, 0.37037037037037035, 0.5714285714285715, 0.8421052631578948, 0.888888888888889, 0.5714285714285715, 0.3333333333333333]
0.76586.011401.0831[0.7, 0.75, 0.7368421052631577, 0.9, 1.0, 0.47058823529411764, 0.8695652173913044, 0.7368421052631577, 0.5, 0.8000000000000002, 0.13333333333333333, 0.761904761904762, 0.7826086956521738, 0.6666666666666666, 0.47619047619047616, 0.7, 0.9, 0.8421052631578948, 0.5714285714285715, 0.4615384615384615]
0.76587.013301.0915[0.7777777777777777, 0.75, 0.6666666666666666, 0.888888888888889, 1.0, 0.4285714285714285, 0.8181818181818182, 0.7368421052631577, 0.47619047619047616, 0.7777777777777777, 0.25, 0.761904761904762, 0.7200000000000001, 0.7499999999999999, 0.56, 0.7368421052631577, 0.9090909090909091, 0.8421052631578948, 0.5333333333333333, 0.4347826086956522]
0.31148.015201.0847[0.761904761904762, 0.7058823529411765, 0.7, 0.9473684210526316, 1.0, 0.4285714285714285, 0.9, 0.7368421052631577, 0.48, 0.8000000000000002, 0.26666666666666666, 0.8, 0.8571428571428572, 0.7777777777777777, 0.5185185185185185, 0.6666666666666665, 0.9, 0.888888888888889, 0.5714285714285715, 0.45454545454545453]
0.31149.017101.0742[0.7777777777777777, 0.7058823529411765, 0.7, 0.9473684210526316, 1.0, 0.4285714285714285, 0.9090909090909091, 0.7368421052631577, 0.5454545454545454, 0.8000000000000002, 0.2857142857142857, 0.7272727272727273, 0.6923076923076923, 0.7499999999999999, 0.5833333333333334, 0.6, 0.8421052631578948, 0.8421052631578948, 0.5714285714285715, 0.4347826086956522]
0.311410.019001.0933[0.7777777777777777, 0.75, 0.7, 0.9473684210526316, 1.0, 0.30769230769230765, 0.9090909090909091, 0.7368421052631577, 0.5217391304347826, 0.8000000000000002, 0.25, 0.761904761904762, 0.6923076923076923, 0.7499999999999999, 0.5, 0.5263157894736842, 0.8421052631578948, 0.8421052631578948, 0.5333333333333333, 0.4347826086956522]

Framework versions

  • —Transformers 4.38.2
  • —Pytorch 2.2.1+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2