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metadata
license: mit
base_model: FacebookAI/roberta-base
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: song-coherency-classifier-v2
    results: []

song-coherency-classifier-v2

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

  • Loss: 0.1341
  • F1: [0.9784946236559139, 0.9789473684210526]

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 1.0 190 0.0924 [0.9760000000000001, 0.9761273209549072]
No log 2.0 380 0.0926 [0.9754768392370572, 0.9766233766233766]
0.1717 3.0 570 0.0825 [0.9810298102981029, 0.9817232375979111]
0.1717 4.0 760 0.0892 [0.9813333333333334, 0.9814323607427056]
0.1717 5.0 950 0.0788 [0.9838709677419355, 0.9842105263157895]
0.0737 6.0 1140 0.1032 [0.9813333333333334, 0.9814323607427056]
0.0737 7.0 1330 0.1212 [0.9783783783783783, 0.9790575916230367]
0.0538 8.0 1520 0.1010 [0.9786096256684492, 0.9788359788359788]
0.0538 9.0 1710 0.1186 [0.9811320754716981, 0.9816272965879265]
0.0538 10.0 1900 0.1341 [0.9784946236559139, 0.9789473684210526]

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1