song-artist-classifier-v6-roberta-batch-16-lr-1e-5
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: 1.2738
- F1: [0.6, 0.8181818181818182, 0.7499999999999999, 0.7368421052631577, 0.7826086956521738, 0.8181818181818182, 0.4210526315789474, 0.7368421052631577, 0.5, 0.8181818181818182, 0.47619047619047616, 0.37499999999999994, 0.22222222222222224, 0.64, 0.7200000000000001, 0.46153846153846156, 0.5454545454545454, 0.7368421052631577, 0.8571428571428571, 0.47619047619047616]
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: 1e-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 | 2.5828 | [0.0, 0.26666666666666666, 0.0, 0.15384615384615383, 0.0, 0.4347826086956522, 0.0, 0.41666666666666663, 0.0, 0.37499999999999994, 0.28571428571428575, 0.0, 0.0, 0.48, 0.4444444444444445, 0.0, 0.2295081967213115, 0.25, 0.0, 0.16666666666666669] |
| No log | 2.0 | 190 | 2.1411 | [0.26666666666666666, 0.5454545454545454, 0.6, 0.25, 0.15384615384615383, 0.5517241379310345, 0.37499999999999994, 0.5454545454545454, 0.18181818181818182, 0.42424242424242425, 0.5263157894736842, 0.48, 0.0, 0.5384615384615384, 0.56, 0.30769230769230765, 0.3157894736842105, 0.4, 0.0, 0.32] |
| No log | 3.0 | 285 | 1.8664 | [0.35294117647058826, 0.6666666666666665, 0.7499999999999999, 0.631578947368421, 0.5263157894736842, 0.6060606060606061, 0.2105263157894737, 0.64, 0.16666666666666669, 0.7200000000000001, 0.47619047619047616, 0.47058823529411764, 0.0, 0.5000000000000001, 0.6956521739130435, 0.3333333333333333, 0.3529411764705882, 0.631578947368421, 0.0, 0.380952380952381] |
| No log | 4.0 | 380 | 1.6537 | [0.4210526315789474, 0.75, 0.7499999999999999, 0.588235294117647, 0.7272727272727272, 0.7200000000000001, 0.22222222222222224, 0.608695652173913, 0.4, 0.7200000000000001, 0.4347826086956522, 0.37499999999999994, 0.0, 0.6153846153846154, 0.6363636363636365, 0.2857142857142857, 0.3157894736842105, 0.7777777777777777, 0.0, 0.380952380952381] |
| No log | 5.0 | 475 | 1.5407 | [0.5, 0.8571428571428572, 0.6666666666666666, 0.7, 0.7272727272727272, 0.7272727272727272, 0.28571428571428564, 0.7, 0.5, 0.8181818181818182, 0.45454545454545453, 0.37499999999999994, 0.0, 0.5714285714285714, 0.7272727272727272, 0.30769230769230765, 0.33333333333333326, 0.6666666666666666, 0.75, 0.47619047619047616] |
| 2.0597 | 6.0 | 570 | 1.4166 | [0.631578947368421, 0.7826086956521738, 0.6666666666666666, 0.7368421052631577, 0.7826086956521738, 0.7200000000000001, 0.2727272727272727, 0.7, 0.4, 0.8181818181818182, 0.5, 0.47058823529411764, 0.22222222222222224, 0.6666666666666666, 0.6956521739130435, 0.42857142857142855, 0.4210526315789474, 0.7777777777777777, 0.75, 0.47619047619047616] |
| 2.0597 | 7.0 | 665 | 1.3629 | [0.6, 0.8, 0.7499999999999999, 0.8000000000000002, 0.7, 0.7777777777777777, 0.4000000000000001, 0.7, 0.5, 0.7200000000000001, 0.5, 0.47058823529411764, 0.4, 0.6956521739130435, 0.6956521739130435, 0.42857142857142855, 0.47619047619047616, 0.6363636363636365, 0.75, 0.5555555555555556] |
| 2.0597 | 8.0 | 760 | 1.3041 | [0.6, 0.7826086956521738, 0.7499999999999999, 0.8000000000000002, 0.7826086956521738, 0.8181818181818182, 0.4000000000000001, 0.7, 0.5, 0.8181818181818182, 0.5, 0.47058823529411764, 0.22222222222222224, 0.6956521739130435, 0.75, 0.46153846153846156, 0.4347826086956522, 0.7368421052631577, 0.75, 0.5555555555555556] |
| 2.0597 | 9.0 | 855 | 1.2953 | [0.6, 0.8181818181818182, 0.7499999999999999, 0.7368421052631577, 0.7826086956521738, 0.8181818181818182, 0.4210526315789474, 0.7368421052631577, 0.5, 0.8181818181818182, 0.47619047619047616, 0.37499999999999994, 0.22222222222222224, 0.64, 0.7200000000000001, 0.46153846153846156, 0.5454545454545454, 0.7368421052631577, 0.8571428571428571, 0.47619047619047616] |
| 2.0597 | 10.0 | 950 | 1.2738 | [0.6, 0.8181818181818182, 0.7499999999999999, 0.7368421052631577, 0.7826086956521738, 0.8181818181818182, 0.4210526315789474, 0.7368421052631577, 0.5, 0.8181818181818182, 0.47619047619047616, 0.37499999999999994, 0.22222222222222224, 0.64, 0.7200000000000001, 0.46153846153846156, 0.5454545454545454, 0.7368421052631577, 0.8571428571428571, 0.47619047619047616] |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2