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song-artist-classifier-v15-segmented_data
tjl223/song-artist-classifier-v15-segmented_data
song-artist-classifier-v15-segmented_data is a text classification model from tjl223. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Mar 31, 2024
- Updated
- Mar 31, 2024
- SHA
- 0558d76b
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
song-artist-classifier-v15-segmented_data
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: 1.3400
- F1: [0.8235294117647058, 0.7142857142857143, 0.6666666666666665, 0.8571428571428571, 0.5714285714285713, 0.631578947368421, 0.47058823529411764, 0.8235294117647058, 0.8, 0.4210526315789474, 0.8000000000000002, 0.7272727272727272, 0.18181818181818182, 0.9, 0.4375, 0.7142857142857143, 0.8421052631578948, 0.26666666666666666, 0.625, 0.631578947368421]
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 |
|---|---|---|---|---|
| 2.3819 | 1.0 | 601 | 1.7801 | [0.16666666666666669, 0.19999999999999998, 0.375, 0.6666666666666666, 0.4347826086956522, 0.16666666666666669, 0.3333333333333333, 0.7499999999999999, 0.7200000000000001, 0.125, 0.631578947368421, 0.5, 0.18181818181818182, 0.5, 0.2777777777777778, 0.4375, 0.7272727272727272, 0.0, 0.0, 0.588235294117647] |
| 1.693 | 2.0 | 1202 | 1.2739 | [0.8421052631578948, 0.3636363636363636, 0.7999999999999999, 0.8571428571428571, 0.34782608695652173, 0.6153846153846154, 0.5263157894736842, 0.6666666666666666, 0.8571428571428572, 0.33333333333333326, 0.8421052631578948, 0.6363636363636365, 0.4, 0.9, 0.5, 0.7200000000000001, 0.7777777777777777, 0.0, 0.5714285714285713, 0.5454545454545454] |
| 1.253 | 3.0 | 1803 | 1.1600 | [0.888888888888889, 0.5, 0.625, 0.8571428571428571, 0.47058823529411764, 0.6666666666666665, 0.47619047619047616, 0.888888888888889, 0.8333333333333333, 0.37499999999999994, 0.8421052631578948, 0.7058823529411764, 0.18181818181818182, 0.8181818181818182, 0.6, 0.6428571428571429, 0.8000000000000002, 0.25, 0.5217391304347826, 0.6666666666666666] |
| 0.9138 | 4.0 | 2404 | 1.3108 | [0.7499999999999999, 0.3636363636363636, 0.7000000000000001, 0.75, 0.47058823529411764, 0.5454545454545454, 0.4000000000000001, 0.888888888888889, 0.7692307692307693, 0.125, 0.761904761904762, 0.6666666666666666, 0.30769230769230765, 0.9, 0.42857142857142855, 0.6060606060606061, 0.7272727272727272, 0.22222222222222224, 0.4444444444444445, 0.588235294117647] |
| 0.4867 | 5.0 | 3005 | 1.3483 | [0.888888888888889, 0.5, 0.7368421052631579, 0.75, 0.6666666666666666, 0.5217391304347826, 0.5263157894736842, 0.8235294117647058, 0.7200000000000001, 0.33333333333333326, 0.7368421052631577, 0.631578947368421, 0.33333333333333337, 0.7200000000000001, 0.41379310344827586, 0.625, 0.761904761904762, 0.22222222222222224, 0.18181818181818182, 0.631578947368421] |
| 0.3353 | 6.0 | 3606 | 1.3618 | [0.9473684210526316, 0.7142857142857143, 0.625, 0.8571428571428571, 0.3529411764705882, 0.3529411764705882, 0.5, 0.7777777777777777, 0.7407407407407407, 0.13333333333333333, 0.7777777777777777, 0.6363636363636365, 0.26666666666666666, 0.9, 0.5, 0.4878048780487805, 0.6666666666666665, 0.2, 0.5263157894736842, 0.5263157894736842] |
| 0.2703 | 7.0 | 4207 | 1.3844 | [0.888888888888889, 0.5, 0.7142857142857143, 0.8571428571428571, 0.5, 0.5, 0.4000000000000001, 0.7777777777777777, 0.8, 0.25, 0.8421052631578948, 0.6666666666666666, 0.16666666666666669, 0.9, 0.47058823529411764, 0.625, 0.7058823529411764, 0.18181818181818182, 0.6666666666666665, 0.7368421052631577] |
| 0.1997 | 8.0 | 4808 | 1.4064 | [0.888888888888889, 0.6153846153846153, 0.4615384615384615, 0.8571428571428571, 0.5, 0.45454545454545453, 0.5263157894736842, 0.761904761904762, 0.8, 0.5, 0.7777777777777777, 0.6666666666666666, 0.15384615384615383, 0.9, 0.5333333333333333, 0.5714285714285715, 0.6666666666666666, 0.3333333333333333, 0.625, 0.6666666666666665] |
| 0.1635 | 9.0 | 5409 | 1.4331 | [0.8235294117647058, 0.6153846153846153, 0.7058823529411765, 0.8571428571428571, 0.47619047619047616, 0.5, 0.4444444444444445, 0.7777777777777777, 0.8, 0.4444444444444445, 0.7368421052631577, 0.761904761904762, 0.16666666666666669, 0.9, 0.48484848484848486, 0.5882352941176471, 0.6666666666666666, 0.2857142857142857, 0.7058823529411764, 0.588235294117647] |
| 0.112 | 10.0 | 6010 | 1.3400 | [0.8235294117647058, 0.7142857142857143, 0.6666666666666665, 0.8571428571428571, 0.5714285714285713, 0.631578947368421, 0.47058823529411764, 0.8235294117647058, 0.8, 0.4210526315789474, 0.8000000000000002, 0.7272727272727272, 0.18181818181818182, 0.9, 0.4375, 0.7142857142857143, 0.8421052631578948, 0.26666666666666666, 0.625, 0.631578947368421] |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Mar 31, 2024
- Updated
- Mar 31, 2024