metadata
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_amh_cross_0.0001
results: []
furina_seed42_eng_kin_amh_cross_0.0001
This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0269
- Spearman Corr: 0.7365
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: 0.0001
- 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 | 0.59 | 200 | 0.0342 | 0.5390 |
No log | 1.17 | 400 | 0.0309 | 0.4762 |
No log | 1.76 | 600 | 0.0333 | 0.6360 |
0.0424 | 2.35 | 800 | 0.0407 | 0.6425 |
0.0424 | 2.93 | 1000 | 0.0304 | 0.6871 |
0.0424 | 3.52 | 1200 | 0.0316 | 0.6953 |
0.0231 | 4.11 | 1400 | 0.0249 | 0.7122 |
0.0231 | 4.69 | 1600 | 0.0405 | 0.7040 |
0.0231 | 5.28 | 1800 | 0.0365 | 0.7094 |
0.0231 | 5.87 | 2000 | 0.0327 | 0.7062 |
0.0155 | 6.45 | 2200 | 0.0258 | 0.6996 |
0.0155 | 7.04 | 2400 | 0.0324 | 0.7080 |
0.0155 | 7.62 | 2600 | 0.0265 | 0.7257 |
0.0095 | 8.21 | 2800 | 0.0297 | 0.7239 |
0.0095 | 8.8 | 3000 | 0.0244 | 0.7276 |
0.0095 | 9.38 | 3200 | 0.0282 | 0.7339 |
0.0095 | 9.97 | 3400 | 0.0290 | 0.7252 |
0.0064 | 10.56 | 3600 | 0.0242 | 0.7284 |
0.0064 | 11.14 | 3800 | 0.0239 | 0.7332 |
0.0064 | 11.73 | 4000 | 0.0248 | 0.7300 |
0.0049 | 12.32 | 4200 | 0.0258 | 0.7320 |
0.0049 | 12.9 | 4400 | 0.0246 | 0.7271 |
0.0049 | 13.49 | 4600 | 0.0269 | 0.7373 |
0.0038 | 14.08 | 4800 | 0.0285 | 0.7336 |
0.0038 | 14.66 | 5000 | 0.0262 | 0.7316 |
0.0038 | 15.25 | 5200 | 0.0279 | 0.7320 |
0.0038 | 15.84 | 5400 | 0.0269 | 0.7365 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2