furina_eng_corr_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: 0.0203
• Spearman Corr: 0.7758

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	1.33	200	0.0216	0.7729
0.0014	2.66	400	0.0212	0.7735
0.0013	3.99	600	0.0214	0.7754
0.0013	5.32	800	0.0215	0.7733
0.0012	6.64	1000	0.0211	0.7700
0.0012	7.97	1200	0.0203	0.7745
0.0012	9.3	1400	0.0204	0.7792
0.0011	10.63	1600	0.0199	0.7773
0.001	11.96	1800	0.0210	0.7735
0.001	13.29	2000	0.0204	0.7755
0.001	14.62	2200	0.0203	0.7734
0.0009	15.95	2400	0.0206	0.7752
0.0009	17.28	2600	0.0205	0.7729
0.0009	18.6	2800	0.0208	0.7732
0.0008	19.93	3000	0.0203	0.7758

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.2