furina_arb_loss_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: 0.0209
- Spearman Corr: 0.7757
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 | 0.85 | 200 | 0.0232 | 0.7718 |
No log | 1.69 | 400 | 0.0227 | 0.7752 |
0.0019 | 2.54 | 600 | 0.0221 | 0.7682 |
0.0019 | 3.38 | 800 | 0.0208 | 0.7710 |
0.0015 | 4.23 | 1000 | 0.0239 | 0.7713 |
0.0015 | 5.07 | 1200 | 0.0217 | 0.7724 |
0.0015 | 5.92 | 1400 | 0.0217 | 0.7678 |
0.0014 | 6.77 | 1600 | 0.0225 | 0.7737 |
0.0014 | 7.61 | 1800 | 0.0222 | 0.7751 |
0.0012 | 8.46 | 2000 | 0.0212 | 0.7740 |
0.0012 | 9.3 | 2200 | 0.0231 | 0.7765 |
0.0015 | 10.15 | 2400 | 0.0209 | 0.7757 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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yihongLiu/furina