song_artist_classifier

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

• Loss: 1.4491
• F1: [0.8181818181818182, 0.7777777777777777, 0.7368421052631577, 0.5714285714285715, 0.2, 0.7058823529411764, 0.8000000000000002, 0.5833333333333334, 0.4615384615384615, 0.761904761904762, 0.7, 0.8181818181818182, 0.4, 0.64, 0.6666666666666666, 0.7272727272727272, 0.7826086956521738, 0.7272727272727272, 0.5263157894736842, 0.37499999999999994]

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	95	1.5590	[0.7368421052631577, 0.7777777777777777, 0.7, 0.6666666666666665, 0.4615384615384615, 0.7, 0.761904761904762, 0.5454545454545454, 0.4285714285714285, 0.7200000000000001, 0.7058823529411764, 0.761904761904762, 0.0, 0.6666666666666666, 0.6428571428571429, 0.7272727272727272, 0.9, 0.761904761904762, 0.6666666666666667, 0.3529411764705882]
No log	2.0	190	1.4491	[0.8181818181818182, 0.7777777777777777, 0.7368421052631577, 0.5714285714285715, 0.2, 0.7058823529411764, 0.8000000000000002, 0.5833333333333334, 0.4615384615384615, 0.761904761904762, 0.7, 0.8181818181818182, 0.4, 0.64, 0.6666666666666666, 0.7272727272727272, 0.7826086956521738, 0.7272727272727272, 0.5263157894736842, 0.37499999999999994]

Framework versions

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