furina_ary_corr_2e-05
This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0211
- Spearman Corr: 0.7761
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: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
---|---|---|---|---|
No log | 0.9 | 200 | 0.0219 | 0.7722 |
No log | 1.8 | 400 | 0.0212 | 0.7719 |
0.0017 | 2.7 | 600 | 0.0212 | 0.7705 |
0.0017 | 3.6 | 800 | 0.0210 | 0.7705 |
0.0016 | 4.5 | 1000 | 0.0212 | 0.7732 |
0.0016 | 5.41 | 1200 | 0.0211 | 0.7715 |
0.0014 | 6.31 | 1400 | 0.0219 | 0.7752 |
0.0014 | 7.21 | 1600 | 0.0213 | 0.7726 |
0.0013 | 8.11 | 1800 | 0.0215 | 0.7717 |
0.0013 | 9.01 | 2000 | 0.0222 | 0.7764 |
0.0013 | 9.91 | 2200 | 0.0212 | 0.7734 |
0.0013 | 10.81 | 2400 | 0.0214 | 0.7714 |
0.0013 | 11.71 | 2600 | 0.0206 | 0.7722 |
0.0012 | 12.61 | 2800 | 0.0222 | 0.7719 |
0.0012 | 13.51 | 3000 | 0.0210 | 0.7723 |
0.0012 | 14.41 | 3200 | 0.0211 | 0.7715 |
0.0012 | 15.32 | 3400 | 0.0206 | 0.7762 |
0.0011 | 16.22 | 3600 | 0.0211 | 0.7761 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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