furina_original_kin-hau-eng_train_spearman_corr
This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0267
- Spearman Corr: 0.7425
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 | 1.59 | 200 | 0.0442 | 0.5364 |
0.0796 | 3.19 | 400 | 0.0280 | 0.6912 |
0.0275 | 4.78 | 600 | 0.0329 | 0.7307 |
0.0199 | 6.37 | 800 | 0.0256 | 0.7473 |
0.015 | 7.97 | 1000 | 0.0275 | 0.7502 |
0.015 | 9.56 | 1200 | 0.0265 | 0.7396 |
0.0127 | 11.16 | 1400 | 0.0264 | 0.7484 |
0.0104 | 12.75 | 1600 | 0.0255 | 0.7467 |
0.0089 | 14.34 | 1800 | 0.0256 | 0.7512 |
0.0079 | 15.94 | 2000 | 0.0270 | 0.7457 |
0.0079 | 17.53 | 2200 | 0.0264 | 0.7420 |
0.0069 | 19.12 | 2400 | 0.0276 | 0.7444 |
0.0062 | 20.72 | 2600 | 0.0265 | 0.7383 |
0.0059 | 22.31 | 2800 | 0.0264 | 0.7416 |
0.0055 | 23.9 | 3000 | 0.0269 | 0.7439 |
0.0055 | 25.5 | 3200 | 0.0268 | 0.7415 |
0.0051 | 27.09 | 3400 | 0.0267 | 0.7425 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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