Loss: 1.1816
F1: [0.26666666666666666, 0.9473684210526316, 0.7368421052631577, 0.45454545454545453, 0.64, 0.8695652173913044, 0.625, 0.761904761904762, 0.4000000000000001, 0.8181818181818182, 0.608695652173913, 0.4285714285714285, 0.18181818181818182, 0.7, 0.6666666666666666, 0.5263157894736842, 0.631578947368421, 0.761904761904762, 0.5, 0.5555555555555556]

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	95	2.5420	[0.0, 0.2745098039215686, 0.0, 0.2631578947368421, 0.0, 0.6428571428571429, 0.10526315789473685, 0.34782608695652173, 0.0, 0.0, 0.17391304347826086, 0.15384615384615383, 0.0, 0.0, 0.26666666666666666, 0.19999999999999998, 0.15384615384615385, 0.18181818181818182, 0.0, 0.0]
No log	2.0	190	2.2216	[0.0, 0.56, 0.5128205128205129, 0.0, 0.3157894736842105, 0.761904761904762, 0.25806451612903225, 0.6363636363636365, 0.0, 0.0, 0.18181818181818182, 0.5333333333333333, 0.4444444444444445, 0.30769230769230765, 0.2622950819672131, 0.4761904761904762, 0.125, 0.0, 0.0, 0.26666666666666666]
No log	3.0	285	1.8928	[0.2222222222222222, 0.6, 0.5714285714285715, 0.47619047619047616, 0.45454545454545453, 0.6060606060606061, 0.28571428571428564, 0.64, 0.11764705882352941, 0.2105263157894737, 0.37499999999999994, 0.5, 0.0, 0.47058823529411764, 0.5925925925925927, 0.26666666666666666, 0.24, 0.23529411764705882, 0.0, 0.3529411764705882]
No log	4.0	380	1.6430	[0.3333333333333333, 0.7272727272727272, 0.7368421052631577, 0.5454545454545454, 0.6, 0.8333333333333333, 0.4285714285714285, 0.7272727272727272, 0.23529411764705882, 0.5294117647058825, 0.4444444444444445, 0.4615384615384615, 0.4, 0.5263157894736842, 0.64, 0.5882352941176471, 0.4, 0.588235294117647, 0.4, 0.5]
No log	5.0	475	1.5263	[0.2857142857142857, 0.8235294117647058, 0.7368421052631577, 0.4666666666666667, 0.6666666666666666, 0.8333333333333333, 0.4347826086956522, 0.7272727272727272, 0.37499999999999994, 0.6363636363636365, 0.5714285714285713, 0.4615384615384615, 0.36363636363636365, 0.5555555555555556, 0.5263157894736842, 0.6666666666666666, 0.48, 0.888888888888889, 0.5714285714285715, 0.47058823529411764]
1.9079	6.0	570	1.3454	[0.5, 0.8421052631578948, 0.7368421052631577, 0.45454545454545453, 0.5714285714285714, 0.8695652173913044, 0.5555555555555556, 0.7272727272727272, 0.30769230769230765, 0.8421052631578948, 0.7272727272727272, 0.47058823529411764, 0.2857142857142857, 0.7, 0.6666666666666665, 0.5882352941176471, 0.5217391304347826, 0.888888888888889, 0.5, 0.5]
1.9079	7.0	665	1.2583	[0.4444444444444445, 0.9, 0.7368421052631577, 0.47619047619047616, 0.6666666666666666, 0.8695652173913044, 0.4285714285714285, 0.7, 0.37499999999999994, 0.7200000000000001, 0.64, 0.5333333333333333, 0.4, 0.7, 0.7368421052631577, 0.6666666666666666, 0.6, 0.761904761904762, 0.5, 0.5]
1.9079	8.0	760	1.2143	[0.39999999999999997, 0.9, 0.6666666666666665, 0.5263157894736842, 0.6923076923076923, 0.8695652173913044, 0.588235294117647, 0.7272727272727272, 0.25, 0.8181818181818182, 0.608695652173913, 0.625, 0.36363636363636365, 0.7368421052631577, 0.7, 0.761904761904762, 0.5714285714285713, 0.761904761904762, 0.5, 0.5555555555555556]
1.9079	9.0	855	1.1913	[0.26666666666666666, 0.9, 0.7368421052631577, 0.45454545454545453, 0.7200000000000001, 0.9090909090909091, 0.5714285714285715, 0.7272727272727272, 0.380952380952381, 0.8181818181818182, 0.608695652173913, 0.4285714285714285, 0.0, 0.7, 0.6666666666666666, 0.6666666666666666, 0.6, 0.761904761904762, 0.5, 0.5555555555555556]
1.9079	10.0	950	1.1816	[0.26666666666666666, 0.9473684210526316, 0.7368421052631577, 0.45454545454545453, 0.64, 0.8695652173913044, 0.625, 0.761904761904762, 0.4000000000000001, 0.8181818181818182, 0.608695652173913, 0.4285714285714285, 0.18181818181818182, 0.7, 0.6666666666666666, 0.5263157894736842, 0.631578947368421, 0.761904761904762, 0.5, 0.5555555555555556]

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

tjl223/song-artist-classifier-v7-alberta

song-artist-classifier-v7-alberta

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tjl223/
song-artist-classifier-v7-alberta