furina_original_amh-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: 0.0307
• Spearman Corr: 0.7768

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	1.55	200	0.0406	0.6987
0.0766	3.1	400	0.0250	0.7633
0.0241	4.65	600	0.0292	0.7707
0.0174	6.2	800	0.0268	0.7797
0.0174	7.75	1000	0.0345	0.7801
0.0137	9.3	1200	0.0285	0.7790
0.0109	10.85	1400	0.0289	0.7754
0.0091	12.4	1600	0.0253	0.7798
0.0078	13.95	1800	0.0273	0.7777
0.0078	15.5	2000	0.0262	0.7698
0.007	17.05	2200	0.0261	0.7736
0.006	18.6	2400	0.0260	0.7761
0.0055	20.16	2600	0.0307	0.7768

Framework versions

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