furina_esp_corr_5e-06
This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0222
- Spearman Corr: 0.7655
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: 5e-06
- 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 | 0.94 | 200 | 0.0219 | 0.7638 |
No log | 1.89 | 400 | 0.0226 | 0.7628 |
0.0039 | 2.83 | 600 | 0.0221 | 0.7654 |
0.0039 | 3.77 | 800 | 0.0214 | 0.7642 |
0.0037 | 4.72 | 1000 | 0.0222 | 0.7630 |
0.0037 | 5.66 | 1200 | 0.0217 | 0.7612 |
0.0035 | 6.6 | 1400 | 0.0229 | 0.7649 |
0.0035 | 7.55 | 1600 | 0.0220 | 0.7641 |
0.0034 | 8.49 | 1800 | 0.0232 | 0.7629 |
0.0034 | 9.43 | 2000 | 0.0227 | 0.7636 |
0.0033 | 10.38 | 2200 | 0.0222 | 0.7655 |
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