furina_latin_original_amh-esp-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: 0.0272
- Spearman Corr: 0.7575
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 | 0.0206 | 0.6547 |
0.0681 | 3.17 | 400 | 0.0237 | 0.7560 |
0.0224 | 4.76 | 600 | 0.0168 | 0.7473 |
0.0172 | 6.35 | 800 | 0.0199 | 0.7406 |
0.0172 | 7.94 | 1000 | 0.0211 | 0.7572 |
0.0138 | 9.52 | 1200 | 0.0223 | 0.7572 |
0.0115 | 11.11 | 1400 | 0.0240 | 0.7514 |
0.0094 | 12.7 | 1600 | 0.0229 | 0.7535 |
0.008 | 14.29 | 1800 | 0.0284 | 0.7531 |
0.008 | 15.87 | 2000 | 0.0220 | 0.7526 |
0.0072 | 17.46 | 2200 | 0.0286 | 0.7588 |
0.0065 | 19.05 | 2400 | 0.0284 | 0.7528 |
0.0058 | 20.63 | 2600 | 0.0230 | 0.7549 |
0.0054 | 22.22 | 2800 | 0.0230 | 0.7565 |
0.0054 | 23.81 | 3000 | 0.0244 | 0.7509 |
0.0052 | 25.4 | 3200 | 0.0255 | 0.7557 |
0.0048 | 26.98 | 3400 | 0.0264 | 0.7572 |
0.0046 | 28.57 | 3600 | 0.0272 | 0.7575 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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