--- license: apache-2.0 base_model: albert/albert-base-v2 tags: - generated_from_trainer metrics: - f1 model-index: - name: song-artist-classifier-v7-alberta results: [] --- # song-artist-classifier-v7-alberta This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset. It achieves the following results on the evaluation set: - 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