furina_amh_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: 0.0237
- Spearman Corr: 0.7697
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 | 0.0232 | 0.7664 |
No log | 1.81 | 400 | 0.0228 | 0.7676 |
0.0039 | 2.71 | 600 | 0.0255 | 0.7675 |
0.0039 | 3.62 | 800 | 0.0235 | 0.7673 |
0.0033 | 4.52 | 1000 | 0.0224 | 0.7712 |
0.0033 | 5.43 | 1200 | 0.0243 | 0.7666 |
0.0039 | 6.33 | 1400 | 0.0223 | 0.7700 |
0.0039 | 7.24 | 1600 | 0.0244 | 0.7631 |
0.0036 | 8.14 | 1800 | 0.0234 | 0.7705 |
0.0036 | 9.05 | 2000 | 0.0224 | 0.7680 |
0.0036 | 9.95 | 2200 | 0.0227 | 0.7673 |
0.0032 | 10.86 | 2400 | 0.0225 | 0.7680 |
0.0032 | 11.76 | 2600 | 0.0242 | 0.7665 |
0.0029 | 12.67 | 2800 | 0.0233 | 0.7671 |
0.0029 | 13.57 | 3000 | 0.0214 | 0.7683 |
0.0027 | 14.48 | 3200 | 0.0217 | 0.7705 |
0.0027 | 15.38 | 3400 | 0.0233 | 0.7675 |
0.0025 | 16.29 | 3600 | 0.0239 | 0.7683 |
0.0025 | 17.19 | 3800 | 0.0231 | 0.7678 |
0.0023 | 18.1 | 4000 | 0.0234 | 0.7692 |
0.0023 | 19.0 | 4200 | 0.0227 | 0.7674 |
0.0023 | 19.91 | 4400 | 0.0230 | 0.7687 |
0.0022 | 20.81 | 4600 | 0.0237 | 0.7697 |
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