furina_kin-amh-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: 0.0282
• Spearman Corr: 0.7381

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	0.59	200	0.0387	0.6212
No log	1.17	400	0.0399	0.6657
No log	1.76	600	0.0315	0.7081
0.0462	2.35	800	0.0248	0.7262
0.0462	2.93	1000	0.0313	0.7265
0.0462	3.52	1200	0.0238	0.7300
0.0199	4.11	1400	0.0279	0.7239
0.0199	4.69	1600	0.0306	0.7390
0.0199	5.28	1800	0.0248	0.7458
0.0199	5.87	2000	0.0221	0.7419
0.0135	6.45	2200	0.0253	0.7466
0.0135	7.04	2400	0.0239	0.7465
0.0135	7.62	2600	0.0295	0.7387
0.0098	8.21	2800	0.0277	0.7404
0.0098	8.8	3000	0.0305	0.7382
0.0098	9.38	3200	0.0266	0.7386
0.0098	9.97	3400	0.0267	0.7350
0.0074	10.56	3600	0.0261	0.7418
0.0074	11.14	3800	0.0282	0.7381

Framework versions

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